Integrated Gene Co-Expression Analysis of Host–Parasite Transcriptomes Reveals Mechanisms of Host Modulation

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However, due to the diverse consequences of parasite infection on host molecular physiology, it can be challenging to identify pathways that are directly targeted by parasites. This applies in particular to non-model systems such as the interaction between the parasitic tapeworm Anomotaenia brevis and its intermediate host, the ant Temnothorax nylanderi, whose phenotype is strongly altered by the infection. By integrating transcriptome information from hosts and their parasites in a combined weighted gene co-expression network analysis (WGCNA), we identified gene networks and candidate genes critical for this parasite-host interaction. Our analysis revealed tight statistical links between the expression of specific parasite genes and key host molecular pathways. The gene networks and correlations identified are consistent with those playing a major role in model parasite-host systems, a validation of our approach. Finally, we gained first insights into the functions of previously unannotated parasite genes, but which can be considered candidates for host manipulation. The expression of genes encoding proteins secreted by the parasite into the host was associated with host genes involved in oxidative stress resistance, metabolism, muscle function, immunity, and cuticular sclerotization, suggesting that the parasite may modulate these molecular pathways in the host. Our findings advance our understanding of parasite interference and highlight key mechanisms in the evolution of these complex molecular interactions. Interactome WGCNA gene networks parasite manipulation social insects Figures Figure 1 Introduction Parasite infections can profoundly alter the phenotypes of their hosts. These changes can be multifaceted and include behavioural shifts [ 1 , 2 ], physiological alterations [ 3 , 4 ] and immunological changes [ 5 ]. While these alterations are often the result of active manipulation by parasites to enhance their fitness [ 6 ], alternative mechanisms may contribute to phenotypic changes of hosts, including selectively neutral or detrimental side-effects of parasite manipulation, interference by other organisms, or host defences [ 6 – 8 ]. Identifying the molecular mechanisms and signalling pathways underlying these phenotypic changes in the host is often challenging, especially in non-model organisms. Investigating the molecular processes that mediate infection-related phenotypic changes in hosts is even more difficult when multiple phenotypes are affected. For example, workers of the ant Temnothorax nylanderi that are infected by the cestode Anomotaenia brevis show diverse phenotypic changes such as sluggish behaviour [ 9 ], muscle dystrophy [ 10 ], significant lifespan extension [ 11 ] and reduced cuticle sclerotization and melanisation [ 12 ]. A. brevis infection can affect up to 10% of the transcriptome of the ants [ 13 ], but the highly diverse changes make the search for the parasite-targeted signalling pathways difficult. In order to identify candidate genes and signalling pathways of the parasite that cause changes in the activity of host genes and pathways, bioinformatic predictions of host-parasite protein interactions (HPPI) are often used [ 14 – 16 ]. While these approaches have proven fruitful in model organisms, they possess several limitations: First, homology-based predictions assume that homologues retain conserved functions, which limits their ability to identify novel gene functions that have developed in the parasite through adaptation to its novel lifestyle and when protein functions have diverged [ 17 , 18 ]. This becomes especially difficult when considering that parasite genomes are often shaped by evolutionary arms races in which the neofunctionalization of genes is common [ 19 ]. Second and third, domain- and motif-based HPPI predictions assume that they interact with functional domains of proteins that bind them. However, these methods are computationally intensive and difficult to perform in non-model species with poorly annotated genomes. Especially for non-model systems, it is demanding to find alternative methods to identify genes in the parasite genome that target molecular pathways in the host. Therefore, we decided to develop a method to analyse the molecular interactions between parasite and host based solely on the transcriptome data of both correlation partners. In this study, we employed a weighted gene co-expression network analysis (WGCNA; 19) to statistically link transcriptomic data of a parasite and its host. Using the host–parasite system Temnothorax nylanderi–Anomotaenia brevis , which exhibits profound parasite-induced shifts in host gene expression, physiology, behaviour and lifespan [ 10 – 12 , 20 , 21 ], we integrated expression data from the haemolymph-residing cysticercoid larvae of the parasitic cestode and the fat body of the ant host from the same individual to build a network consisting of modules of co-expressed genes of both the host and the parasite. If the parasite actively shapes the transcriptional activity of the host, we predicted that the expression of parasite genes that are involved in the manipulation would be strongly correlated to the expression of host genes that underpin the phenotypic changes. This would result in the expression of some cestode genes being more strongly associated with the expression of specific host genes than with other parasite genes, and in a weaker link among host genes. This approach allowed us to identify parasite genes whose expression is linked to host genes and signalling pathways, and thus to gain first functional insights into uncharacterized genes of both species potentially important for their interaction. From the host perspective, we identified gene networks that are tightly intertwined with the parasite transcriptome, enabling us to describe the molecular consequences of parasitism on host physiology. By analysing the gene ontology of these networks, we identified associated biological processes in the host, providing additional insights into the interactome of the parasite and its host. Furthermore, leveraging the recent publication of the A. brevis secretome [ 22 ], we evaluated the potential roles of secreted proteins, whose functions were previously unknown due to a lack of annotation, by analysing their correlations to host genes. This straightforward and integrative approach, which can also be applied to other non-model systems, can shed light on the molecular mechanisms governing parasite-host interactions. Material and Methods We obtained our data from the published dataset of Sistermans et al. (2025; methodological details see supplement[ 13 ]), the raw reads of which can be found on the SRA database of NCBI (PRJNA1246159), and the gene count matrices, GO terms and KEGG terms on Dryad (DOI: 10.5061/dryad.8cz8w9h3b ). We combined the gene count matrices of Anomotaenia brevis cysticercoid larvae and the fat bodies of infected Temnothorax nylanderi worker ants. We focused on the fat body as the target tissue because, in insects, this physiologically active organ is responsible for synthesizing and processing proteins essential for immunity, fecundity, and longevity [ 23 ]. Gene counts were paired per sample (table S1 ); as both originated from the same worker ant. This process yielded a joint gene count matrix for 15 infected samples, encompassing transcripts from both cestode and ant genes (Table S1 ). From this combined matrix, we filtered out genes with fewer than ten counts in at least five samples and verified the data for missing entries using the WGCNA package [ 24 ] in R (version 4.3.2). To construct an unsigned co-expression network, we set the soft-thresholding power to 8. After testing various module sizes, we established a minimum module size of 100, and confirmed this using a TOM plot. Modules with a dissimilarity threshold of 0.2 were merged, and the result was validated with an additional TOM plot (Fig. S1 ). We identified hub genes by selecting the genes with the top 10% highest connectivity within their modules. We used a chi-square test per module to check whether there were more cestode hub genes than would be expected by chance. For this, we used the proportion of cestode genes per module as the expected variable, the proportion of cestode hub genes as the observed variable and the number of hub genes as the sample size. We corrected the p-values for multiple testing using Benjamini-Hochberg adjustment. We then converted our topological overlap matrix into Cytoscape objects [ 25 ] for each module to identify correlations between two genes and their weight. In this way, we were able to visually confirm a deeper integration of specific cestode genes into ant gene networks and vice versa. Cytoscape objects were used to assess whether genes from one species within a module were more likely to correlate with genes from the other species. Assuming random interactions, the null hypothesis predicted that a gene would interact proportionally to the ratio of ant and cestode genes within the module (e.g., a 50:50 ratio would predict equal correlations with genes from both species). Although gene expression within the same species is likely to be more strongly statistically linked, we tested against the more conservative null hypothesis of random interactions. We calculated the proportion of genes interacting with cestode genes for both ant and cestode genes in each module and tested deviations from the null hypothesis using a chi-square test, with the number of ant or cestode genes in each module as the sample size. P-values were adjusted for multiple testing using the Benjamini-Hochberg method. In addition, we investigated genes of the cestode that are actively released as proteins into the host haemolymph [ 22 ]. We selected the 15 most abundant cestode genes in the ant haemolymph proteome and all annotated genes among the 50 most abundant genes. These genes were used as queries for a DIAMOND BLAST search against a custom database created from our genome coding sequences (CDS), which were translated using TransDecoder v5.5.0 [ 26 ]. For each query, the most frequently expressed gene among the BLAST hits was selected to identify the corresponding genes in the proteome. Using these identified genes, we determined the modules in which they were located and evaluated whether these modules contained ant or cestode gene clusters that were more strongly associated with the other species. Confidence intervals were calculated for these modules, and we tested whether these genes were more likely to interact with the other species by verifying whether they fell outside the 95% confidence interval. We also identified the ant genes these cestode genes interacted with and performed GO and KEGG enrichment analyses for these ant genes to assess their potential functions, the files for the GO and KEGG enrichment were also derived from Sistermans et al. 2025 [ 13 ]. Results For our analysis we combined gene count matrices of both hosts and their corresponding parasites and analysed the correlation of each gene in WGCNA. Upon combining both parasite and host gene count matrices, we identified 18 WGCNA modules from a total of 20,806 genes, including 9,472 cestode genes and 11,334 ant genes. Module sizes ranged from 261 to 5,751 genes (Fig. 1 a). These modules encompassed genes from both species, with the proportion of cestode genes per module varying between 0.02 and 0.8 (Fig. 1 a). When identifying hub genes—those with the top 10% connectivity—we demonstrated that in most modules, the proportion of hub genes significantly differed from the overall proportion of genes from each species within the respective module (Fig. 1 b; p-values found in Table 1 , column 5). Notably, in two modules, all hub genes originated from the host, while in six modules, all hub genes were cestode genes. Overall, 11 out of 18 modules exhibited a significantly higher proportion of the hub genes being cestode genes compared to ant genes (Table 1 ). In these modules, the proportion of cestode genes ranged from 0.55 to 0.8. Table 1 Statistical results on the interactome modules, in the two rows with the P-adjusted values for differential correlation the black values signify correlations more strongly towards the other species while the grey values signify stronger correlations towards the own species. Whenever a p-value is in bold it is either significant or the genes correlate significantly more with the other species. Module ID Proportion of cestode genes P-adjusted ant genes correlating differently than proportion of ant-cestode genes P-adjusted cestode genes correlating differently than proportion of ant-cestode genes P-adjusted cestode genes hub representation compared to proportion Black 0.61 < 0.0001 0.0001 < 0.0001 Blue 0.06 0.002 1 < 0.002 Brown 0.55 < 0.0001 < 0.0001 < 0.0001 Cyan 0.79 0.01 < 0.0001 0.0007 Darkgreen 0.08 0.12 1 1 Darkorange 0.75 0.0002 < 0.0001 < 0.0001 Darkred 0.15 0.19 1 0.40 Greenyellow 0.79 0.07 0.001 0.003 Grey 0.23 0.31 1 1 Grey60 0.02 0.31 1 1 Lightcyan 0.54 0.0002 0.0003 < 0.0001 Lightgreen 0.19 0.0003 1 0.26 Lightyellow 0.75 0.11 0.001 0.03 Magenta 0.09 0.0008 1 0.19 Midnightblue 0.03 0.31 1 1 Pink 0.08 < 0.0001 1 0.01 Royalblue 0.70 0.31 0.0008 0.02 Turquoise 0.80 < 0.0001 < 0.0001 < 0.0001 Visualization of the networks through Cytoscape [ 25 ] revealed a high level of integration and interspecific gene correlations (Fig. 1 c). This was further supported by the correlation analysis, where we tested whether genes from one species were more likely to correlate with those of the other species than expected under the null hypothesis, which we set as the same value as the proportion of ant/cestode genes in the module. Thus if the proportion of cestode genes was 0.5, we tested whether cestode gene correlation partners comprised of 50% cestode genes and 50% ant genes, or whether this significantly differed in either direction. After p-value adjustment, we identified six modules in which ant genes were significantly more likely to correlate with cestode genes than expected by chance (Table 1 ). In contrast, we found no modules where cestode genes exhibited higher-than-expected correlations with ant genes. Correlation partners of abundant cestode proteins in the ant haemolymph Cysticercoid larvae of A. brevis , which reside in the haemolymph loosely attached to the gut of their host, have been shown to secrete proteins into the host's haemolymph [ 22 ]. We identified four annotated and twelve unannotated transcripts of the most abundant cestode proteins in our dataset (Fig. 1 d; Table 2 ) and identified the correlation partners of these genes separately. The four annotated genes include thioredoxin peroxidase and superoxide dismutase (black module), lysosomal alpha-glucosidase (brown module), and a putative protein disulfide isomerase ER 60 (dark orange module). These genes exhibited correlation patterns that differed from what their proportional representation in the modules would predict (Table 2 ). Specifically, superoxide dismutase interacted predominantly with ant genes, whereas the other genes showed stronger links to cestode genes than expected (Table 2 ). Table 2 Expression links of genes most abundant in the cestode secretome with ant or cestode genes. Ranking based on their abundance in the ants’ haemolymph in which the cysticercoid stages of this tapeworm parasite reside. We report the module these genes belong to, the gene name as reported in Hartke et al. (2023), the proportion of cestode genes they correlates with, proportion of cestode genes in the module, standard error, lower bound and upper bound for the confidence interval and finally the expression to which species ‘ genes this gene is linked to (ant, cestode or non-significant). Gene ranking Module colour Gene name Prop. cestode genes correlated with Prop. of cestode genes in module SE Lower bound Upper bound Significant 1 Turquoise TRINITY_DN231_c0_g2_i2_1 0.988 0.869 0.007 0.854 0.883 Ant 2 Dark orange TRINITY_DN141_c0_g1_i5_2 0.855 0.889 0.012 0.865 0.912 Cestode 3 Dark orange TRINITY_DN66_c1_g1_i1_3 0.914 0.889 0.012 0.865 0.912 Ant 4 Turquoise TRINITY_DN943_c0_g1_i2_4 0.824 0.869 0.007 0.854 0.883 Cestode 5 Grey TRINITY_DN143_c0_g1_i9_5 0.4 0.372 0.065 0.244 0.5 N.S. 6 Turquoise TRINITY_DN199_c0_g2_i1_6 0.945 0.869 0.007 0.854 0.883 Ant 8 Light yellow TRINITY_DN211_c0_g1_i5_8 0.857 0.884 0.02 0.845 0.922 N.S. 9 Black TRINITY_DN4073_c0_g2_i2_9_thioredoxin_peroxidase 0.652 0.714 0.016 0.684 0.745 Cestode 10 Royal blue TRINITY_DN53_c1_g1_i7_10 0.934 0.858 0.023 0.813 0.903 Ant 12 Dark orange TRINITY_DN25_c0_g2_i4_12 0.843 0.889 0.012 0.865 0.912 Cestode 13 Dark orange TRINITY_DN81_c0_g1_i7_13 0.882 0.889 0.012 0.865 0.912 N.S. 14 Royal blue TRINITY_DN117_c0_g1_i9_14 0.827 0.858 0.023 0.813 0.903 N.S. 15 Dark orange TRINITY_DN22_c0_g1_i4_15 0.94 0.889 0.012 0.865 0.912 Ant 22 Black TRINITY_DN897_c0_g1_i2_22_superoxide_dismutase 0.778 0.714 0.016 0.684 0.745 Ant 31 Dark orange TRINITY_DN3503_c0_g2_i2_31_putative_protein_disulfide_isomerase_ER_60 0.828 0.889 0.012 0.865 0.912 Cestode 42 Brown TRINITY_DN16034_c0_g1_i1_42_lysosomal_alpha_glucosidase 0.581 0.665 0.008 0.648 0.681 Cestode Notably, two of these genes, protein disulfide isomerase and alpha-glucosidase , were identified as hub genes. Gene Ontology (GO) enrichment analysis of the ant correlation partners of these genes (Fig. 1 e) revealed significant GO terms associated with their functions. For the ant genes that were statistically linked to the cestode superoxide dismutase , two enriched GO terms were identified: cation transmembrane transport (GO:0098655; 10 genes; for a statistics overview of all significant GO terms of annotated genes, see table S2) and response to electrical stimulus involved in regulation of muscle adaptation (GO:0014878; 2 genes). Transmembrane transport of cations can cause an increase in Reactive Oxygen Species (ROS) [ 27 ], and muscle contractions do the same [ 28 ], possibly explaining the link between this cestode gene and ant genes with those functionalities. These findings align with the established role of superoxide dismutase in regulating oxidative stress, as demonstrated in model organisms such as Caenorhabditis elegans [ 29 ], and its expression has also been associated with increased lifespan in queens of several social insects [ 30 – 32 ]. In parasitic helminths, superoxide dismutase can play a role in defence against ROS originating from the host [ 33 ]. In the same module (black), we found another antioxidant, thioredoxin peroxidase [ 34 ], which is involved in the regulation of oxidative stress associated with normal aerobic metabolism [ 35 ]. This aligns with the enriched GO terms of the interacting host genes, which include several metabolic processes such as proteasome-mediated ubiquitin-dependent protein catabolism (GO:0043161; table S2), peptidyl-threonine dephosphorylation (GO:0035970), and regulation of transcriptional start site selection at the RNA polymerase II promoter (GO:0001178). Additionally, pathways involved in the ant's defence against oxidative stress were identified, including ADP transport (GO:0015866), where ADP plays a protective role in mitigating oxidative stress [ 36 ]. The concordance between these results and our findings for superoxide dismutase may stem from the significant overlap in interacting host genes. Notably, 190 of the 191 interacting partners of superoxide dismutase were also among the 428 interacting partners of thioredoxin peroxidase . The third gene, the putative protein disulfide isomerase ER 60 , belongs to a gene family known to influence parasite virulence [ 37 ] and its downregulation in parasitic nematodes can increase parasite mortality in host plants [ 38 ]. The most common GO term, represented by four genes, is mating (GO:0007618; table S2), a process in which disulfide isomerases appear to play a direct role. In vertebrates, disulfide isomerases have been shown to function as chaperones for ADAM3, a protein whose misfolding can result in male infertility [ 39 ]. In parasites, this gene can reduce host fertility by increasing the production of secretory proteins, which leads to a reduction in mating factor binding [ 40 ]. This function as a chaperone for secretory proteins could explain the GO term positive regulation of calcium ion-dependent exocytosis with two genes. Exocytosis is an important part of the secretory pathway [ 41 ]. The final annotated gene for which we identified correlation partners is lysosomal alpha-glucosidase from the brown module. This gene plays a fundamental role in basal metabolism by breaking down glycogen and releasing glucose from long-term energy storage [ 42 ]. In cestodes, the expression of another glucosidase, beta-glucosidase, has been shown to correlate negatively with the expression of a host beta-glucosidase [ 43 ]. When we investigated whether an ant host alpha-glucosidase was present among the correlation partners of the cestode lysosomal alpha-glucosidase , we not only identified its presence but also demonstrated a correlation between their expressions using a linear model (p = 0.03, r = 0.113; Fig. S2). Analysis of GO terms enriched in the list of the correlation partners of lysosomal alpha-glucosidase revealed the term regulation of cellular protein metabolic process (GO:0032268; table S2) with 174 genes. This metabolic pathway is intertwined with glucose metabolism and glycolysis [ 44 ]. We find further connection to glucose metabolism with the term response to osmotic stress (GO:0006970; 12 genes), which can be linked to altered glucose concentrations [ 45 ]. Alpha-glucosidases can also influence neuromuscular functions and a deficiency can cause motor and respiratory disorders, known as Pompe disease in vertebrates [ 46 ]. Therefore, unsurprisingly, the most common GO term is neuron projection development (GO:0031175) with 106 genes. Pompe disease decreases glycogen concentration in projection neurons [ 47 ]. Additionally, we identified a GO term associated with cuticle development, specifically the chitin-based embryonic cuticle biosynthetic process (GO:0008362). This may be relevant, as chitin-containing materials are known to act as inhibitors of alpha-glucosidase [ 48 ] and infected ants that become infected during the larval stage exhibit a reduced sclerotization and melanisation of the cuticle during the pupal stage. We also obtained the GO terms for host correlation partners of six commonly secreted cestode proteins that could not be annotated [ 22 ]. Four of these genes were located in the dark orange module, representing the second, third, twelfth, and thirteenth most abundant parasitic proteins in the ant haemolymph, while two were in the turquoise module, corresponding to the fourth and sixth most abundant proteins (Fig. 1 f). The second most abundant gene had 97 correlation partners and was associated with three significant GO terms, all based on two genes (Fig. 1 f). One of these terms is SMAD protein signal transduction (GO:0060395; for a statistics overview of all significant GO terms of unannotated genes, see table S3), a signalling pathway involved in muscle hypertrophy and the negative regulation of muscle growth [ 49 ]. This term co-occurs with positive regulation of cardiac muscle hypertrophy (GO:0010613). Further examination of other candidates in the dark orange module revealed that these cestode genes also strongly interact with genes involved in the SMAD signalling pathway ( SMAD protein signal transduction , GO:0060395; 13th most abundant protein; table S3) and other muscle-related functions, including neuromuscular process controlling posture (GO:0050884), positive regulation of cardiac muscle hypertrophy (GO:0010613), and adult walking behaviour (GO:0007628; 12th most abundant protein; table S3). Given that infected ants exhibit symptoms of muscular dystrophy [ 10 ] and are much less active [ 9 ], these interactions may provide insight into the molecular mechanisms underlying the observed muscle dysfunction. We also identified two immune-related functions among these interacting host genes, including the melanin biosynthetic process (GO:0042438), which plays a critical role in the encapsulation of foreign substances [ 50 ] and negative regulation of lamellocyte differentiation (GO:0035204), lamellocytes being key insect immune cells [ 51 ]. We detected a high degree of coherence in the GO terms among the correlation partners of the fourth and sixth most abundant cestode proteins in the ant haemolymph, both of which are part of the turquoise module. These proteins interact with host genes enriched for tyrosine catabolic process (GO:0006572) and L-phenylalanine catabolic process (GO:0006559). Notably, the tyrosine pathway is involved in sclerotization and melanisation of the insect cuticle [ 52 ], another GO term of which can be found in cuticle hydrocarbon biosynthetic process (GO:0006723) interacting with the fourth most expressed gene. Moreover, phenylalanine catabolism plays a crucial role in the encapsulation of malaria parasites in mosquitoes. When phenylalanine catabolism is disrupted, for example, through the silencing of phenylalanine hydroxylase, this encapsulation process is impaired [ 53 ] and mosquitoes became unable to encapsulate malaria parasites [ 54 ]. The expression of the fourth most abundant protein is associated with host genes involved in lipogenesis, for which we identified nine enriched GO terms (GO:0010873, GO:0043651, GO:1903966, GO:0035338, GO:0036109, GO:0034625, GO:0034626, GO:0019367 and GO:0019367; table S3). Considering that the fat body is the most important immune organ in insects [ 55 ], fat metabolism and immunity are likely closely interconnected. While our GO analysis did not identify specific immune functions beyond L-phenylalanine catabolic process (GO:0006559) and the response to cobalt ion (GO:0032025) involved in detoxification, the involvement of genes in lipogenesis may provide insights into how the immune system of infected ants is altered. For instance, in Drosophila lipogenesis is suppressed by the Toll signalling pathway during periods of immune stress [ 56 ], and lipids themselves can play a role in the immune responses against fungal parasites [ 57 ]. Discussion Through our novel application of the Weighted Gene Co-expression Network Analysis (WGCNA) in a joint dataset of individual host and parasite transcriptomes, we have gained significant insights into how host and parasite transcriptional activities are intertwined. Our findings reveal that the expression of cestode genes is linked to a substantially greater number of genes compared to host genes. In six modules, ant genes were more likely to correlate with cestode genes than with other host genes. Notably, within these modules, cestode genes primarily interacted with other cestode genes. This pattern appears to be achieved via a reduction in the linkage of ant gene expression to other genes, contrasting with the extensive connectivity observed among cestode genes. This effect is particularly evident in the hub genes of these modules. In modules where ant genes correlated more frequently with cestode genes, the representation of hub genes was overwhelmingly dominated by cestode genes. One plausible explanation is that A. brevis has evolved to exploit the molecular physiology of T. nylanderi , with a substantial proportion of the parasite's expressed genes interacting with host genes. By contrast, T. nylanderi interacts not only with the cestode but also with nestmates and the broader biotic and abiotic environment, so that its transcriptionally activity is less shaped by its parasite. For instance, consider a scenario where the host is challenged by a pathogenic infection. To combat the threat, the host must activate its immune system, altering gene expression in the fat body. Such activation is likely to have minimal effects on the rest of the host's gene expression. For the cestode, on the other hand, a host immune challenge may necessitate activating its own immune defences to prevent hyperparasitism, leading to significant shifts in its gene expression [ 58 , 59 ], to regulate the host’s immune system upon immune challenge [ 60 ] and adapt to a possibly more hostile environment caused by the immune response [ 61 ]. This would mean the co-expression between the parasite’s stress responses, immune system, parasite-host communication with only the host’s immune system. When considering the scenario where the parasite directly influences the host gene expression, the parasite would be more likely to benefit from fewer changes, thus the parasite might even take the burden of gene expression change compared to the host. Besides the larger gene expression patterns in parasite and host, we demonstrated the correlation partners of genes whose proteins are commonly secreted into the ant haemolymph. For the annotated genes, we observed that their functions were closely associated with biological processes in the ant that were either analogous to, or likely influenced by, the functions of these genes in parasites. First, we highlight the oxidative stress genes superoxide dismutase and thioredoxin peroxidase . Our analysis revealed highly interactive expression between these two genes. They were clustered within the same module, with superoxide dismutase correlating with all but one of the genes that thioredoxin peroxidase also interacted with. This finding aligns with previous studies, which have shown that superoxide dismutase and thioredoxin peroxidase function within the same oxidative stress pathway in systems without parasite involvement [ 62 ] and in parasitic cestodes [ 35 ]. The genes they correlate with indicate that their primary role is not necessarily in direct communication with the host but rather in defence against the oxidative stress generated by the host. It has been hypothesized that thioredoxin peroxidase , in particular, is secreted by parasites into the host primarily to modulate oxidative stress, which arises naturally in the host through aerobic metabolism [ 35 , 63 ]. This conclusion is supported by the observation that the associated gene functions are primarily involved in metabolism and correlate with other genes that mitigate oxidative stress in the host. It is plausible that this modulation of oxidative stress contributes to the significantly extended lifespan of the host. However, the high level of secretion of these proteins may not have originally evolved for this purpose, as these genes are among the most frequently expressed in many parasite-host systems [ 64 ]. Thus, their contribution to lifespan extension could be an incidental by-product rather than an adaptive trait. What becomes evident from the presence of thioredoxin peroxidase is that A. brevis seems to be able to thrive in its cysticercoid stage in an aerobic environment within the host. This ability is notable, as Platyhelminthes are known to adapt to anaerobic environments at various life stages [ 65 ]. For disulfide isomerase , we found that its correlation partners are predominantly linked to secretion, consistent with the established functions of disulfide isomerases in parasites and other systems [ 66 , 67 ]. The last annotated gene, alpha-glucosidase , also supports this interpretation. Similar to previous findings with beta-glucosidase [ 43 ], we observed a negative correlation between parasite alpha-glucosidase and host alpha-glucosidase . Additionally, its correlation partners are associated with glucose metabolism. Alpha-glucosidases are enzymes that catalyse the breakdown of polymeric glucose variants, such as starch or glycogen, into glucose monomers (63). This gene is thus a strong candidate for involvement in the cestode's nutrient acquisition, as glucose uptake is critical for cestode survival and growth [ 68 ]. This activity contrasts with the expected reduction of glycogen levels in infected hosts. Interestingly, metacestode-infected beetles have been reported to exhibit increased glycogen levels (65), potentially as a compensatory response to maintain stable glycogen reserves in the presence of cestode alpha-glucosidase . This interplay highlights the intricate metabolic interactions between host and parasite. Finally, we discuss the functions of host genes whose expression is associated with as-yet unannotated proteins secreted into the ant's haemolymph. The four genes in the dark orange module may play a role in manipulating the host's behaviour and morphology. Among the host genes associated with these proteins, we identified functions related to muscle development and the SMAD signalling pathway. This suggests that these cestode genes could influence the host's muscle development, potentially contributing to observed changes in host behaviour and morphology [ 10 ]. Although A. brevis has never been found in the host’s brain, there have been reports on parasites whose infection causes behavioural alterations in social insects while not being present in the brain [ 69 , 70 ]. This would additionally explain the presence of the GO term of walking behaviour. Given these clues we believe these genes to be strong candidates for involvement the host’s sluggish behaviour and we believe the high abundance of their protein products in the haemolymph might serve as a clue for the fact that these proteins need to travel all the way to the host’s brain. Additionally, the two cestode genes identified in the turquoise module appear to play a role in suppressing the immune response, potentially with the side effect of inhibiting cuticle sclerotization. This hypothesis is supported by the identification of numerous genes associated with lipogenesis and direct immune functions in this module. Alternatively, this suppression could represent a response to the host’s immune activity or rather the suppression of the host’s immune system, which cestodes are known to be able to do [ 71 ]. Due to this study being limited on the fact that correlation does not mean causation we propose that future experiments focus on this pathway in the host. In adult ants, the silencing of these genes might re-activate the immune response towards the parasite, leading to the possible overexpression of serine proteases, which are involved in immune avoidance in cestodes [ 72 , 73 ] and has been shown to be affected by parasite load in this system [ 20 ]. Finally, the expression of these genes should also be tested in cestode-infected larvae to test whether these genes in any way correlate to ant genes that are involved in the melanisation of the cuticle. This way it would be possible to link parasite immune suppression to a key phenotypic trait of infected ants [ 12 ]. Conclusion In summary, our analysis demonstrates a remarkable integration of the parasite's transcriptome into the host's, with the high connectivity of parasite genes indicating a sustained, active correlation between the two and cestode genes being present in every single module. Through our novel application of WGCNA, we identified numerous candidate genes with previously unknown functions, while known candidate genes aligned well with findings from other studies. These results highlight the effectiveness of this approach in elucidating the interactome between parasite and host, particularly in non-model organisms. Abbreviations WGCNA – Weighted Gene Co-Expression Network Analysis, GO – Gene Ontology, BLAST -Basic Local Alignment Search Tool, KEGG – Kyoto Encyclopedia for Genes and Genomes, TOM plot – Topological Overlap Matrix plot. Declarations Ethics approval and consent to participate Not applicable Consent to publish Not applicable. Competing interests The authors declare that they have no competing interests Funding This project was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)—GRK2526/1—Project no. 407023052. Author Contribution Conceptualization T.S. and S.F.. Transcriptome analysis T.S. with consultation of R.L.. Original draft writing T.S. with revision comments from R.L and S.F.. Funding S.F. Acknowledgements Not applicable. Data Availability We obtained our data from the published dataset of Sistermans et al. (2025; methodological details see supplement[13]), the raw reads of which can be found on the SRA database of NCBI (PRJNA1246159), and the gene count matrices, GO terms and KEGG terms on Dryad (DOI: 10.5061/dryad.8cz8w9h3b). References Evans HC, Elliot SL, Hughes DP. Ophiocordyceps unilateralis. 2011;4:598–602. https://doi.org/0.1371/journal.pone . Weinersmith K, Faulkes Z. Parasitic manipulation of hosts’ phenotype, or how to make a zombie - An introduction to the symposium. Integrative and Comparative Biology. 2014;54:93–100. https://doi.org/10.1093/icb/icu028 Høeg JT. The biology and life cycle of the Rhizocephala (Cirripedia). Journal of the Marine Biological Association of the United Kingdom. 1995;75:517–50. https://doi.org/10.1017/S0025315400038996 Tobias ZJC, Fowler AE, Blakeslee AMH, Darling JA, Torchin ME, Miller AW, et al. Invasion history shapes host transcriptomic response to a body-snatching parasite. Mol Ecol. 2021;30:4321–37. https://doi.org/10.1111/mec.16038 . Vuitton DA. The ambiguous role of immunity in echinococcosis: protection of the host or of the parasite? Acta Trop. 2003;85:119–32. Poulin R, Maure F. Host Manipulation by Parasites: A Look Back Before Moving Forward. Trends Parasitol. 2015;31:563–70. https://doi.org/10.1016/j.pt.2015.07.002 . Cézilly F, Thomas F, Médoc V, Perrot-Minnot MJ. Host-manipulation by parasites with complex life cycles: adaptive or not? Trends Parasitol. 2010;26:311–7. https://doi.org/10.1016/j.pt.2010.03.009 . Poulin R, Brodeur J, Moore J. Parasite Manipulation of Host Behaviour: Should Hosts Always Lose? Oikos. 1994;70:479–84. Beros S, Jongepier E, Hagemeier F, Foitzik S. The parasite’s long arm: A tapeworm parasite induces behavioural changes in uninfected group members of its social host. Proceedings of the Royal Society B: Biological Sciences. 2015;282. https://doi.org/10.1098/rspb.2015.1473 Feldmeyer B, Mazur J, Beros S, Lerp H, Binder H, Foitzik S. Gene expression patterns underlying parasite-induced alterations in host behaviour and life history. Mol Ecol. 2016;25:648–60. https://doi.org/10.1111/mec.13498 . Beros S, Lenhart A, Scharf I, Negroni MA, Menzel F, Foitzik S. Extreme lifespan extension in tapeworm-infected ant workers. Royal Soc Open Sci. 2021;8. https://doi.org/10.1098/rsos.202118 . Trabalon M, Plateaux L, Péru L, Bagnères AG, Hartmann N. Modification of morphological characters and cuticular compounds in worker ants Leptothorax nylanderi induced by endoparasites Anomotaenia brevis. J Insect Physiol. 2000;46:169–78. https://doi.org/10.1016/S0022-1910(99)00113-4 . Sistermans T, Darras H, Rognet V, Beros S, Hartke J, Stoldt M, et al. Parasite prevalence in a social host has colony-wide impacts on transcriptional activity and survival. Evolution. 2025;qpaf118. https://doi.org/10.1093/evolut/qpaf118 . Davis FP, Barkan DT, Eswar N, Mckerrow JH, Sali A. Host – pathogen protein interactions predicted by comparative modeling. Protein Sci. 2009. https://doi.org/10.1110/ps.073228407.6 . Dyer MD, Murali TM, Sobral BW. Computational prediction of host-pathogen protein – protein interactions. Bioinformatics. 2007. https://doi.org/10.1093/bioinformatics/btm208 . Soyemi J, Isewon I, Oyelade J, Adebiyi E. Inter-Species/Host-Parasite Protein Interaction Predictions Reviewed. 2018;:396–406. https://doi.org/10.2174/1574893613666180108155851 Jackson AP. Genome evolution in trypanosomatid parasites. Parasitology. 2015;142:S40–56. https://doi.org/10.1017/S0031182014000894 . Pan G, Xu J, Li T, Xia Q, Liu S-L, Zhang G, et al. Comparative genomics of parasitic silkworm microsporidia reveal an association between genome expansion and host adaptation. BMC Genomics. 2013;14:186. https://doi.org/10.1186/1471-2164-14-186 . Lynch VJ. Inventing an arsenal: adaptive evolution and neofunctionalization of snake venom phospholipase A2 genes. BMC Evol Biol. 2007;7:2. https://doi.org/10.1186/1471-2148-7-2 . Sistermans T, Hartke J, Stoldt M, Libbrecht R, Foitzik S. The influence of parasite load on transcriptional activity and morphology of a cestode and its ant intermediate host. Mol Ecol. 2023;4412–26. https://doi.org/10.1111/mec.16995 . Stoldt M, Klein L, Beros S, Butter F, Jongepier E, Feldmeyer B, et al. Parasite presence induces gene expression changes in an ant host related to immunity and longevity. Genes. 2021;12. https://doi.org/10.3390/genes12010095 . Hartke J, Ceron-Noriega A, Stoldt M, Sistermans T, Kever M, Fuchs J, et al. Long live the host ! Proteomic analysis reveals possible strategies for parasitic manipulation of its social host. Mol Ecol. 2023;32:5877–89. https://doi.org/10.1111/mec.17155 . Arrese EL, Soulages JL. Insect fat body: Energy, metabolism, and regulation. Ann Rev Entomol. 2010;55:207–25. https://doi.org/10.1146/annurev-ento-112408-085356 . Langfelder P, Horvath S. WGCNA: An R package for weighted correlation network analysis. BMC Bioinformatics. 2008. https://doi.org/10.1186/1471-2105-9-559 . 9. Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, et al. Cytoscape: A Software Environment for Integrated Models. Genome Res. 2003;13:426. https://doi.org/10.1101/gr.1239303.metabolite . Haas BJ, Papanicolaou A, Yassour M, Grabherr M, Blood PD, Bowden J, et al. De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis. Nat Protoc. 2013;8:1494–512. https://doi.org/10.1038/nprot.2013.084 . Dow JAT. The essential roles of metal ions in insect homeostasis and physiology. Curr Opin Insect Sci. 2017;23:43–50. https://doi.org/10.1016/j.cois.2017.07.001 . Powers SK, Ji LL, Kavazis AN, Jackson MJ. Reactive oxygen species: impact on skeletal muscle. Compr Physiol. 2011;1:941–69. https://doi.org/10.1002/cphy.c100054.REACTIVE . Yang W, Li J, Hekimi S. A measurable increase in oxidative damage due to reduction in superoxide detoxification fails to shorten the life span of long-lived mitochondrial mutants of Caenorhabditis elegans. Genetics. 2007;177:2063–74. https://doi.org/10.1534/genetics.107.080788 . Negroni MA, Foitzik S, Feldmeyer B. Long-lived Temnothorax ant queens switch from investment in immunity to antioxidant production with age. Sci Rep. 2019;9:1–10. https://doi.org/10.1038/s41598-019-43796-1 . Parker JD, Parker KM, Sohal BH, Sohal RS. Decreased expression of Cu-Zn superoxide dismutase 1 in ants with extreme lifespan. Proc Natl Acad Sci USA. 2004;101:3486–9. https://doi.org/10.1073/pnas.0400222101 . Tasaki E, Kobayashi K, Matsuura K, Iuchi Y. Long-Lived Termite Queens Exhibit High Cu/Zn-Superoxide Dismutase Activity. Hindawi. 2018. Calvani END, De Marco Verissimo C, Jewhurst HL, Cwiklinski K, Flaus A, Dalton JP. Two Distinct Superoxidase Dismutases (SOD) Secreted by the Helminth Parasite Fasciola hepatica Play Roles in Defence against Metabolic and Host Immune Cell-Derived Reactive Oxygen Species (ROS) during Growth and Development. Antioxidants. 2022;11:1–20. McGonigle S, Curley GP, Dalton JP. Cloning of peroxiredoxin, a novel antioxidant enzyme, from the helminth parasite Fasciola hepatica. Parasitology. 1997;115:101–4. Salinas G, Fernandez V, Fernandez C, Selkirk ME. Echinococcus granulosus: Cloning of a Thioredoxin Peroxidase. Exp Parasitol. 1998;90:298–301. Sokolova N, Pan S, Provazza S, Beutner G, Vendelin M, Birkedal R. ADP Protects Cardiac Mitochondria under Severe Oxidative Stress. PLoS ONE. 2013. https://doi.org/10.1371/journal.pone.0083214 . 8. Achour YB, Chenik M, Louzir H, Dellagi K. Identification of a Disulfide Isomerase Protein of Leishmania major as a Putative Virulence Factor. Fungal and parasitic infections. 2002;70:3576–85. https://doi.org/10.1128/IAI.70.7.3576 Habash SS, Miroslaw S, Siddique S, Voigt B, Elashry A, Grundler FWM. Identification and characterization of a putative protein disulfide isomerase (HsPDI) as an alleged effector of Heterodera schachtii. Sci Rep. 2017;7. https://doi.org/10.1038/s41598-017-13418-9 . Tokuhiro K, Ikawa M, Benham AM, Okabe M. Protein disul fi de isomerase homolog PDILT is required for quality control of sperm membrane protein ADAM3 and male fertility. Proc Natl Acad Sci USA. 2012;109:3850–5. https://doi.org/10.1073/pnas.1117963109 . Inan M, Aryasomayajula D, Sinha J, Meagher MM. Enhancement of Protein Secretion in Pichia pastoris by Overexpression of Protein Disulfide Isomerase. Biotechnol Bioeng. 2006;93:771–8. https://doi.org/10.1002/bit.20762 . Baker PF, Knight DE. Exocytosis: control by calcium and other factors. Br Med Bull. 1986;42:399–404. Hermans MMP, Kroos MA, Van Beeumen J, Oostra BA, Reuser AJJ. Human lysosomal α-glucosidase: Characterization of the catalytic site. J Biol Chem. 1991;266:13507–12. https://doi.org/10.1016/s0021-9258(18)92727-4 . Vysotskaya RU, Krupnova MY, Ieshko EP, Anikieva LV, Lebedeva DI. Ecological and biochemical aspects of parasite-host interactions in transformed aquatic bodies: A case study of the cestode Triaenophorus nodulosus and its host, the northern pike Esox lucius. Biology Bull. 2015;42:246–53. https://doi.org/10.1134/S1062359015030140 . Carthew RW. Gene Regulation and Cellular Metabolism: An Essential Partnership. Trends Genet. 2022;37:389–400. https://doi.org/10.1016/j.tig.2020.09.018.Gene . Albertyn J, Hohmann S, Prior BA. Characterization of the osmotic-stress response in Saccharomyces cerevisiae: osmotic stress and glucose repression regulate glycerol-3-phosphate dehydrogenase independently. Curr Genet. 1994;25:12–8. Colella P, Sellier P, Gomez MJ, Biferi MG, Tanniou G, Guerchet N, et al. Gene therapy with secreted acid alpha-glucosidase rescues Pompe disease in a novel mouse model with early-onset spinal cord and respiratory defects. EBioMedicine. 2020;61. https://doi.org/10.1016/j.ebiom.2020.103052 . Sidman RL, Taksir T, Fidler J, Zhao M, James C, Passini MA, et al. Temporal Neuropathological and Behavioral Phenotype of 6neo/6neo Pompe Disease Mice. J Neuropathol Exp Neurol. 2009;67:803–18. https://doi.org/10.1097/NEN.0b013e3181815994.Temporal . Nguyen VB, Wang S-L. Reclamation of Marine Chitinous Materials for the Production of α -Glucosidase Inhibitors via. Mar Drugs. 2017;15. https://doi.org/10.3390/md15110350 . Nikooie R, Jafari-Sardoie S, Sheibani V, Chatroudi AN. Resistance training - induced muscle hypertrophy is mediated by TGF‐β 1‐Smad signaling pathway in male Wistar rats. J Cell Physiol. 2020;235:5649–65. https://doi.org/10.1002/jcp.29497 . Gillespie JP, Kanost MR, Trenczek T. Biological mediators of insect immunity. Ann Rev Entomol. 1997;42:661–643. Lavine MD, Strand MR. Insect hemocytes and their role in immunity. Insect Biochem Mol Biol. 2002;32:1295–309. Liu C, Yamamoto K, Cheng T-C, Kadono-Okuda K, Narukawa J, Liu S-P, et al. Repression of tyrosine hydroxylase is responsible for the sex-linked chocolate mutation of the silkworm, Bombyx mori. Proc Natl Acad Sci U S A. 2010;107:12980–5. https://doi.org/10.1073/pnas.1001725107 . Calvo AC, Pey AL, Ying M, Loer CM, Martinez A. Anabolic function of phenylalanine hydroxylase in Caenorhabditis elegans. FASEB J. 2008;22:2601–3096. https://doi.org/10.1096/fj.08-108522 . Fuchs S, Behrends V, Bundy JG, Crisanti A, Nolan T. Phenylalanine Metabolism Regulates Reproduction and Parasite Melanization in the Malaria Mosquito. PLoS ONE. 2014;9. https://doi.org/10.1371/journal.pone.0084865 . Hoffmann JA, Reichhart J. Drosophila innate immunity: an evolutionary perspective. Nat Immunol. 2002;3:121–6. Diangelo JR, Bland ML, Bambina S, Cherry S, Birnbaum MJ. The immune response attenuates growth and nutrient storage in Drosophila by reducing insulin signaling. Proc Natl Acad Sci USA. 2009;106:20853–8. https://doi.org/10.1073/pnas.0906749106 . Wronska AK, Kaczmarek A, Bogus MI, Kuna A. Lipids as a key element of insect defense systems. Front Genet. 2023;14. https://doi.org/10.3389/fgene.2023.1183659 . Parratt SR, Laine AL. Pathogen dynamics under both bottom-up host resistance and top-down hyperparasite attack. J Appl Ecol. 2018;55:2976–85. https://doi.org/10.1111/1365-2664.13185 . Pirovino M, Iseli C, Curran JA, Conrad B. Birth of immunity in early life: stepwise emergence of resistance and immunity to complex molecular parasites via progressively degenerating hyperparasites. bioRxiv. 2023. Hernandez JLR, Leung G, McKay DM. Cestode regulation of inflammation and inflammatory diseases. Int J Parasitol. 2013;43:233–43. https://doi.org/10.1016/j.ijpara.2012.09.005 . Mideo N. Parasite adaptations to within-host competition. Evolutionary Parasitol. 2009;25:261–8. https://doi.org/10.1016/j.pt.2009.03.001 . Pedrajas JR, Carreras A, Valderrama R, Barroso JB. Mitochondrial 1-Cys-peroxiredoxin/thioredoxin system protects manganese-containing superoxide dismutase (Mn-SOD) against inactivation by peroxynitrite in Saccharomyces cerevisiae. Nitric Oxide - Biology Chem. 2010;23:206–13. https://doi.org/10.1016/j.niox.2010.06.004 . Halliwell B, Gutteridge JMC. Free Radicals in Biology and Medicine. Oxford: Oxford University Press; 1989. Chehayeb JF, Robertson AP, Martin RJ, Geary TG. Proteomic Analysis of Adult Ascaris suum Fluid Compartments and Secretory Products. PLoS Negl Trop Dis. 2014;8. https://doi.org/10.1371/journal.pntd.0002939 . Martínez-González J, de Guevara-Flores J, Del Arenal Mena A. Evolutionary Adaptations of Parasitic Flatworms to Different Oxygen Tensions. Antioxidants. 2022;11. https://doi.org/10.3390/antiox11061102 . Naguleswaran A, Alaeddine F, Guionaud C, Vonlaufen N, Sonda S, Jenoe P, et al. Neospora caninum protein disulfide isomerase is involved in tachyzoite-host cell interaction. Int J Parasitol. 2005;35:1459–72. https://doi.org/10.1016/j.ijpara.2005.06.006 . Stolf BS, Smyrnias I, Lopes LR, Vendramin A, Goto H, Laurindo FRM, et al. Protein disulfide isomerase and host-pathogen interaction. TheScientificWorldJournal. 2011;11:1749–61. https://doi.org/10.1100/2011/289182 . Kashiide T, Kikuta S, Yamaguchi M, Irie T, Kouguchi H, Yagi K, et al. Molecular and functional characterization of glucose transporter genes of the fox tapeworm Echinococcus multilocularis. Mol Biochem Parasitol. 2018;225:7–14. https://doi.org/10.1016/j.molbiopara.2018.08.004 . Beani L. Crazy wasps: when parasites manipulate the Polistes phenotype. Ann Zool Fenn. 2006;43:564–74. Hughes DP, Kathirithamby J, Turillazzi S, Beani L. Social wasps desert the colony and aggregate outside if parasitized: parasite manipulation? Behav Ecol. 2004;15:1037–43. https://doi.org/10.1093/beheco/arh111 . Vendelova E, Lutz MB, Hrčková G. Immunity and immune modulation elicited by the larval cestode Mesocestoides vogae and its products. Parasite Immunol. 2015;37:493–504. https://doi.org/10.1111/pim.12216 . Izvekova GI, Frolova TV. Proteolytic enzymes and their inhibitors in cestodes. Biology Bull Reviews. 2017;7:150–9. https://doi.org/10.1134/s2079086417020049 . Patel S. A critical review on serine protease: Key immune manipulator and pathology mediator. Allergol Immunopathol. 2017;45:579–91. https://doi.org/10.1016/j.aller.2016.10.011 . Jongepier E, Séguret A, Labutin A, Feldmeyer B, Gstöttl C, Foitzik S, et al. Convergent Loss of Chemoreceptors across Independent Origins of Slave-Making in Ants. Mol Biol Evol. 2022;39. https://doi.org/10.1093/molbev/msab305 . Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, et al. Seq Anal. 2013;29:15–21. https://doi.org/10.1093/bioinformatics/bts635 . Zanini F, Anders S, Pyl PT, Pimanda JE. Gene expression Analysing high-throughput sequencing data in Python with HTSeq 2. 0. 2022;38 March:2943–5. Wingett SW, Andrews S. Fastq screen: A tool for multi-genome mapping and quality control [version 1; referees: 3 approved, 1 approved with reservations]. F1000Research. 2018;7 May:1–13. https://doi.org/10.12688/f1000research.15931.1 Chen S, Zhou Y, Chen Y, Gu J, Fastp. An ultra-fast all-in-one FASTQ preprocessor. Bioinformatics. 2018;34:i884–90. https://doi.org/10.1093/bioinformatics/bty560 . Kim D, Langmead B, Salzberg SL. HISAT: A fast spliced aligner with low memory requirements. Nat Methods. 2015;12:357–60. https://doi.org/10.1038/nmeth.3317 . Pertea M, Pertea GM, Antonescu CM, Chang TC, Mendell JT, Salzberg SL. StringTie enables improved reconstruction of a transcriptome from RNA-seq reads. Nat Biotechnol. 2015;33:290–5. https://doi.org/10.1038/nbt.3122 . Buchfink B, Xie C, Huson DH. Fast and sensitive protein alignment using DIAMOND. Nat Methods. 2014;12:59–63. https://doi.org/10.1038/nmeth.3176 . Cantalapiedra CP, Hern̗andez-Plaza A, Letunic I, Bork P, Huerta-Cepas J. eggNOG-mapper v2: Functional Annotation, Orthology Assignments, and Domain Prediction at the Metagenomic Scale. Mol Biol Evol. 2021;38:5825–9. https://doi.org/10.1093/molbev/msab293 . Additional Declarations No competing interests reported. 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07:48:44","extension":"html","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":195173,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7789718/v1/29e290d59dac0ec4d9cb2bc2.html"},{"id":94634273,"identity":"6a21957d-2a63-4998-94c3-f0b8716393b3","added_by":"auto","created_at":"2025-10-29 06:42:59","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":932440,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eResults of the Interactome Analysis. A. WGCNA Modules and Gene Representation. \u003c/strong\u003eThis panel shows the distribution of genes within each module, differentiated by species. Cestode genes are represented in pink, while ant genes are represented in brown. The size of each module is indicated on the x-axis alongside the module names. \u003cstrong\u003eB. Hub Gene Representation \u003c/strong\u003eThis panel illustrates the hub gene representation within each module, using the same colour scheme as Panel A. The number of hub genes is specified next to the respective module names, module names in bold are significantly overrepresented by cestode genes. \u003cstrong\u003eC. Gene correlations within the Grey Module \u003c/strong\u003eThis network plot represents all significant correlations within the grey module. Each dot corresponds to an individual gene, and each edge represents a significant correlation between genes. Cestode genes are shown as pink dots, and ant genes are shown as brown dots. Note that the distance between nodes does not indicate the strength of correlation. \u003cstrong\u003eD. Gene Module Membership of Cestode Genes\u003c/strong\u003e\u003cbr\u003e\nThe left plot displays the module membership of all cestode genes, while the right plot highlights the module membership of the 19 most commonly identified cestode genes in the secretome, based on Hartke et al. (2023) [22]. \u003cstrong\u003eE. GO Enrichment of Ant Correlation Partners for Annotated Cestode Genes \u003c/strong\u003eThis panel highlights the Gene Ontology (GO) enrichment of ant correlation partners for annotated common cestode genes found in the ant hemolymph. Different colours represent individual genes. \u003cstrong\u003eF. GO Enrichment of Ant Correlation Partners for Unannotated Cestode Genes. \u003c/strong\u003eThis panel shows GO enrichment for ant correlation partners of unannotated common cestode genes. The colours represent the correlation partners of individual genes, with the order of commonality specified on the right of the bars.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7789718/v1/e51a5599753e74a641f84d04.png"},{"id":101690819,"identity":"7b73f197-1ba6-4e81-83d2-5e822a3d0516","added_by":"auto","created_at":"2026-02-02 16:09:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2019386,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7789718/v1/9f6faa38-6dad-42ab-ae69-a12f79a1e6d0.pdf"},{"id":94641041,"identity":"ac3d8c50-cbf8-49c3-8dd3-80860c025166","added_by":"auto","created_at":"2025-10-29 07:50:30","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":511345,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementarymaterialsmsinteractomeBMC.docx","url":"https://assets-eu.researchsquare.com/files/rs-7789718/v1/6a27b1d4cd76f79a2c433cc8.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Integrated Gene Co-Expression Analysis of Host–Parasite Transcriptomes Reveals Mechanisms of Host Modulation","fulltext":[{"header":"Introduction","content":"\u003cp\u003eParasite infections can profoundly alter the phenotypes of their hosts. These changes can be multifaceted and include behavioural shifts [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], physiological alterations [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] and immunological changes [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. While these alterations are often the result of active manipulation by parasites to enhance their fitness [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], alternative mechanisms may contribute to phenotypic changes of hosts, including selectively neutral or detrimental side-effects of parasite manipulation, interference by other organisms, or host defences [\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Identifying the molecular mechanisms and signalling pathways underlying these phenotypic changes in the host is often challenging, especially in non-model organisms.\u003c/p\u003e\u003cp\u003eInvestigating the molecular processes that mediate infection-related phenotypic changes in hosts is even more difficult when multiple phenotypes are affected. For example, workers of the ant \u003cem\u003eTemnothorax nylanderi\u003c/em\u003e that are infected by the cestode \u003cem\u003eAnomotaenia brevis\u003c/em\u003e show diverse phenotypic changes such as sluggish behaviour [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], muscle dystrophy [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], significant lifespan extension [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] and reduced cuticle sclerotization and melanisation [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. \u003cem\u003eA. brevis\u003c/em\u003e infection can affect up to 10% of the transcriptome of the ants [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], but the highly diverse changes make the search for the parasite-targeted signalling pathways difficult.\u003c/p\u003e\u003cp\u003eIn order to identify candidate genes and signalling pathways of the parasite that cause changes in the activity of host genes and pathways, bioinformatic predictions of host-parasite protein interactions (HPPI) are often used [\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. While these approaches have proven fruitful in model organisms, they possess several limitations: First, homology-based predictions assume that homologues retain conserved functions, which limits their ability to identify novel gene functions that have developed in the parasite through adaptation to its novel lifestyle and when protein functions have diverged [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. This becomes especially difficult when considering that parasite genomes are often shaped by evolutionary arms races in which the neofunctionalization of genes is common [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Second and third, domain- and motif-based HPPI predictions assume that they interact with functional domains of proteins that bind them. However, these methods are computationally intensive and difficult to perform in non-model species with poorly annotated genomes. Especially for non-model systems, it is demanding to find alternative methods to identify genes in the parasite genome that target molecular pathways in the host. Therefore, we decided to develop a method to analyse the molecular interactions between parasite and host based solely on the transcriptome data of both correlation partners.\u003c/p\u003e\u003cp\u003eIn this study, we employed a weighted gene co-expression network analysis (WGCNA; 19) to statistically link transcriptomic data of a parasite and its host. Using the host\u0026ndash;parasite system \u003cem\u003eTemnothorax nylanderi\u0026ndash;Anomotaenia brevis\u003c/em\u003e, which exhibits profound parasite-induced shifts in host gene expression, physiology, behaviour and lifespan [\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], we integrated expression data from the haemolymph-residing cysticercoid larvae of the parasitic cestode and the fat body of the ant host from the same individual to build a network consisting of modules of co-expressed genes of both the host and the parasite. If the parasite actively shapes the transcriptional activity of the host, we predicted that the expression of parasite genes that are involved in the manipulation would be strongly correlated to the expression of host genes that underpin the phenotypic changes. This would result in the expression of some cestode genes being more strongly associated with the expression of specific host genes than with other parasite genes, and in a weaker link among host genes. This approach allowed us to identify parasite genes whose expression is linked to host genes and signalling pathways, and thus to gain first functional insights into uncharacterized genes of both species potentially important for their interaction. From the host perspective, we identified gene networks that are tightly intertwined with the parasite transcriptome, enabling us to describe the molecular consequences of parasitism on host physiology. By analysing the gene ontology of these networks, we identified associated biological processes in the host, providing additional insights into the interactome of the parasite and its host. Furthermore, leveraging the recent publication of the \u003cem\u003eA. brevis\u003c/em\u003e secretome [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], we evaluated the potential roles of secreted proteins, whose functions were previously unknown due to a lack of annotation, by analysing their correlations to host genes. This straightforward and integrative approach, which can also be applied to other non-model systems, can shed light on the molecular mechanisms governing parasite-host interactions.\u003c/p\u003e"},{"header":"Material and Methods","content":"\u003cp\u003eWe obtained our data from the published dataset of Sistermans et al. (2025; methodological details see supplement[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]), the raw reads of which can be found on the SRA database of NCBI (PRJNA1246159), and the gene count matrices, GO terms and KEGG terms on Dryad (DOI: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.5061/dryad.8cz8w9h3b\u003c/span\u003e\u003cspan address=\"10.5061/dryad.8cz8w9h3b\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). We combined the gene count matrices of \u003cem\u003eAnomotaenia brevis\u003c/em\u003e cysticercoid larvae and the fat bodies of infected \u003cem\u003eTemnothorax nylanderi\u003c/em\u003e worker ants. We focused on the fat body as the target tissue because, in insects, this physiologically active organ is responsible for synthesizing and processing proteins essential for immunity, fecundity, and longevity [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Gene counts were paired per sample (table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e); as both originated from the same worker ant. This process yielded a joint gene count matrix for 15 infected samples, encompassing transcripts from both cestode and ant genes (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). From this combined matrix, we filtered out genes with fewer than ten counts in at least five samples and verified the data for missing entries using the WGCNA package [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] in R (version 4.3.2). To construct an unsigned co-expression network, we set the soft-thresholding power to 8. After testing various module sizes, we established a minimum module size of 100, and confirmed this using a TOM plot. Modules with a dissimilarity threshold of 0.2 were merged, and the result was validated with an additional TOM plot (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). We identified hub genes by selecting the genes with the top 10% highest connectivity within their modules. We used a chi-square test per module to check whether there were more cestode hub genes than would be expected by chance. For this, we used the proportion of cestode genes per module as the expected variable, the proportion of cestode hub genes as the observed variable and the number of hub genes as the sample size. We corrected the p-values for multiple testing using Benjamini-Hochberg adjustment. We then converted our topological overlap matrix into Cytoscape objects [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] for each module to identify correlations between two genes and their weight. In this way, we were able to visually confirm a deeper integration of specific cestode genes into ant gene networks and vice versa. Cytoscape objects were used to assess whether genes from one species within a module were more likely to correlate with genes from the other species. Assuming random interactions, the null hypothesis predicted that a gene would interact proportionally to the ratio of ant and cestode genes within the module (e.g., a 50:50 ratio would predict equal correlations with genes from both species). Although gene expression within the same species is likely to be more strongly statistically linked, we tested against the more conservative null hypothesis of random interactions. We calculated the proportion of genes interacting with cestode genes for both ant and cestode genes in each module and tested deviations from the null hypothesis using a chi-square test, with the number of ant or cestode genes in each module as the sample size. P-values were adjusted for multiple testing using the Benjamini-Hochberg method.\u003c/p\u003e\u003cp\u003eIn addition, we investigated genes of the cestode that are actively released as proteins into the host haemolymph [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. We selected the 15 most abundant cestode genes in the ant haemolymph proteome and all annotated genes among the 50 most abundant genes. These genes were used as queries for a DIAMOND BLAST search against a custom database created from our genome coding sequences (CDS), which were translated using TransDecoder v5.5.0 [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. For each query, the most frequently expressed gene among the BLAST hits was selected to identify the corresponding genes in the proteome. Using these identified genes, we determined the modules in which they were located and evaluated whether these modules contained ant or cestode gene clusters that were more strongly associated with the other species. Confidence intervals were calculated for these modules, and we tested whether these genes were more likely to interact with the other species by verifying whether they fell outside the 95% confidence interval. We also identified the ant genes these cestode genes interacted with and performed GO and KEGG enrichment analyses for these ant genes to assess their potential functions, the files for the GO and KEGG enrichment were also derived from Sistermans et al. 2025 [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eFor our analysis we combined gene count matrices of both hosts and their corresponding parasites and analysed the correlation of each gene in WGCNA. Upon combining both parasite and host gene count matrices, we identified 18 WGCNA modules from a total of 20,806 genes, including 9,472 cestode genes and 11,334 ant genes. Module sizes ranged from 261 to 5,751 genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). These modules encompassed genes from both species, with the proportion of cestode genes per module varying between 0.02 and 0.8 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). When identifying hub genes\u0026mdash;those with the top 10% connectivity\u0026mdash;we demonstrated that in most modules, the proportion of hub genes significantly differed from the overall proportion of genes from each species within the respective module (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb; p-values found in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, column 5). Notably, in two modules, all hub genes originated from the host, while in six modules, all hub genes were cestode genes. Overall, 11 out of 18 modules exhibited a significantly higher proportion of the hub genes being cestode genes compared to ant genes (Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In these modules, the proportion of cestode genes ranged from 0.55 to 0.8.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eStatistical results on the interactome modules, in the two rows with the P-adjusted values for differential correlation the black values signify correlations more strongly towards the other species while the grey values signify stronger correlations towards the own species. Whenever a p-value is in bold it is either significant or the genes correlate significantly more with the other species.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eModule ID\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eProportion of cestode genes\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eP-adjusted ant genes 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colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.0002\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDarkred\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.40\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGreenyellow\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGrey\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGrey60\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLightcyan\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.0002\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLightgreen\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.26\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLightyellow\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.03\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMagenta\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0008\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.19\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMidnightblue\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePink\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eRoyalblue\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.0008\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.02\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTurquoise\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eVisualization of the networks through Cytoscape [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] revealed a high level of integration and interspecific gene correlations (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec). This was further supported by the correlation analysis, where we tested whether genes from one species were more likely to correlate with those of the other species than expected under the null hypothesis, which we set as the same value as the proportion of ant/cestode genes in the module. Thus if the proportion of cestode genes was 0.5, we tested whether cestode gene correlation partners comprised of 50% cestode genes and 50% ant genes, or whether this significantly differed in either direction. After p-value adjustment, we identified six modules in which ant genes were significantly more likely to correlate with cestode genes than expected by chance (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In contrast, we found no modules where cestode genes exhibited higher-than-expected correlations with ant genes.\u003c/p\u003e\n\u003ch3\u003eCorrelation partners of abundant cestode proteins in the ant haemolymph\u003c/h3\u003e\n\u003cp\u003eCysticercoid larvae of \u003cem\u003eA. brevis\u003c/em\u003e, which reside in the haemolymph loosely attached to the gut of their host, have been shown to secrete proteins into the host's haemolymph [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. We identified four annotated and twelve unannotated transcripts of the most abundant cestode proteins in our dataset (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ed; Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) and identified the correlation partners of these genes separately. The four annotated genes include \u003cem\u003ethioredoxin peroxidase\u003c/em\u003e and \u003cem\u003esuperoxide dismutase\u003c/em\u003e (black module), \u003cem\u003elysosomal alpha-glucosidase\u003c/em\u003e (brown module), and a putative \u003cem\u003eprotein disulfide isomerase ER 60\u003c/em\u003e (dark orange module). These genes exhibited correlation patterns that differed from what their proportional representation in the modules would predict (Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Specifically, \u003cem\u003esuperoxide dismutase\u003c/em\u003e interacted predominantly with ant genes, whereas the other genes showed stronger links to cestode genes than expected (Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eExpression links of genes most abundant in the cestode secretome with ant or cestode genes. Ranking based on their abundance in the ants\u0026rsquo; haemolymph in which the cysticercoid stages of this tapeworm parasite reside. We report the module these genes belong to, the gene name as reported in Hartke et al. (2023), the proportion of cestode genes they correlates with, proportion of cestode genes in the module, standard error, lower bound and upper bound for the confidence interval and finally the expression to which species \u0026lsquo; genes this gene is linked to (ant, cestode or non-significant).\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGene ranking\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eModule colour\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGene name\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eProp. cestode genes correlated with\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eProp. of cestode genes in module\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eSE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eLower bound\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eUpper bound\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eSignificant\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTurquoise\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTRINITY_DN231_c0_g2_i2_1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.988\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.869\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.854\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.883\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eAnt\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDark orange\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTRINITY_DN141_c0_g1_i5_2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.855\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.889\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.865\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.912\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eCestode\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDark orange\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTRINITY_DN66_c1_g1_i1_3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.914\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.889\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.865\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.912\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eAnt\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTurquoise\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTRINITY_DN943_c0_g1_i2_4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.824\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.869\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.854\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.883\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eCestode\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGrey\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTRINITY_DN143_c0_g1_i9_5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.372\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.065\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.244\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eN.S.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTurquoise\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTRINITY_DN199_c0_g2_i1_6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.945\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.869\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.854\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.883\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eAnt\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLight yellow\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTRINITY_DN211_c0_g1_i5_8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.857\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.884\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.845\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.922\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eN.S.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBlack\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTRINITY_DN4073_c0_g2_i2_9_thioredoxin_peroxidase\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.652\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.714\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.016\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.684\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.745\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eCestode\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRoyal blue\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTRINITY_DN53_c1_g1_i7_10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.934\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.858\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.023\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.813\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.903\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eAnt\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDark orange\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTRINITY_DN25_c0_g2_i4_12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.843\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.889\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.865\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.912\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eCestode\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDark orange\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTRINITY_DN81_c0_g1_i7_13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.882\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.889\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.865\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.912\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eN.S.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRoyal blue\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTRINITY_DN117_c0_g1_i9_14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.827\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.858\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.023\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.813\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.903\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eN.S.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDark orange\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTRINITY_DN22_c0_g1_i4_15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.889\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.865\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.912\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eAnt\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBlack\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTRINITY_DN897_c0_g1_i2_22_superoxide_dismutase\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.778\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.714\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.016\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.684\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.745\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eAnt\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDark orange\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTRINITY_DN3503_c0_g2_i2_31_putative_protein_disulfide_isomerase_ER_60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.828\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.889\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.865\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.912\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eCestode\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBrown\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTRINITY_DN16034_c0_g1_i1_42_lysosomal_alpha_glucosidase\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.581\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.665\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.008\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.648\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.681\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eCestode\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eNotably, two of these genes, \u003cem\u003eprotein disulfide isomerase\u003c/em\u003e and \u003cem\u003ealpha-glucosidase\u003c/em\u003e, were identified as hub genes. Gene Ontology (GO) enrichment analysis of the ant correlation partners of these genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ee) revealed significant GO terms associated with their functions. For the ant genes that were statistically linked to the cestode \u003cem\u003esuperoxide dismutase\u003c/em\u003e, two enriched GO terms were identified: \u003cem\u003ecation transmembrane transport\u003c/em\u003e (GO:0098655; 10 genes; for a statistics overview of all significant GO terms of annotated genes, see table S2) and \u003cem\u003eresponse to electrical stimulus involved in regulation of muscle adaptation\u003c/em\u003e (GO:0014878; 2 genes). Transmembrane transport of cations can cause an increase in Reactive Oxygen Species (ROS) [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], and muscle contractions do the same [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], possibly explaining the link between this cestode gene and ant genes with those functionalities. These findings align with the established role of \u003cem\u003esuperoxide dismutase\u003c/em\u003e in regulating oxidative stress, as demonstrated in model organisms such as \u003cem\u003eCaenorhabditis elegans\u003c/em\u003e [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], and its expression has also been associated with increased lifespan in queens of several social insects [\u003cspan additionalcitationids=\"CR31\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. In parasitic helminths, \u003cem\u003esuperoxide dismutase\u003c/em\u003e can play a role in defence against ROS originating from the host [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. In the same module (black), we found another antioxidant, \u003cem\u003ethioredoxin peroxidase\u003c/em\u003e [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], which is involved in the regulation of oxidative stress associated with normal aerobic metabolism [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. This aligns with the enriched GO terms of the interacting host genes, which include several metabolic processes such as \u003cem\u003eproteasome-mediated ubiquitin-dependent protein catabolism\u003c/em\u003e (GO:0043161; table S2), \u003cem\u003epeptidyl-threonine dephosphorylation\u003c/em\u003e (GO:0035970), and \u003cem\u003eregulation of transcriptional start site selection at the RNA polymerase II promoter\u003c/em\u003e (GO:0001178). Additionally, pathways involved in the ant's defence against oxidative stress were identified, including \u003cem\u003eADP transport\u003c/em\u003e (GO:0015866), where ADP plays a protective role in mitigating oxidative stress [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. The concordance between these results and our findings for \u003cem\u003esuperoxide dismutase\u003c/em\u003e may stem from the significant overlap in interacting host genes. Notably, 190 of the 191 interacting partners of \u003cem\u003esuperoxide dismutase\u003c/em\u003e were also among the 428 interacting partners of \u003cem\u003ethioredoxin peroxidase\u003c/em\u003e.\u003c/p\u003e\u003cp\u003eThe third gene, the putative \u003cem\u003eprotein disulfide isomerase ER 60\u003c/em\u003e, belongs to a gene family known to influence parasite virulence [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] and its downregulation in parasitic nematodes can increase parasite mortality in host plants [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. The most common GO term, represented by four genes, is \u003cem\u003emating\u003c/em\u003e (GO:0007618; table S2), a process in which disulfide isomerases appear to play a direct role. In vertebrates, disulfide isomerases have been shown to function as chaperones for ADAM3, a protein whose misfolding can result in male infertility [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. In parasites, this gene can reduce host fertility by increasing the production of secretory proteins, which leads to a reduction in mating factor binding [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. This function as a chaperone for secretory proteins could explain the GO term positive regulation of calcium ion-dependent exocytosis with two genes. Exocytosis is an important part of the secretory pathway [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. The final annotated gene for which we identified correlation partners is \u003cem\u003elysosomal alpha-glucosidase\u003c/em\u003e from the brown module. This gene plays a fundamental role in basal metabolism by breaking down glycogen and releasing glucose from long-term energy storage [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. In cestodes, the expression of another glucosidase, beta-glucosidase, has been shown to correlate negatively with the expression of a host beta-glucosidase [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. When we investigated whether an ant host \u003cem\u003ealpha-glucosidase\u003c/em\u003e was present among the correlation partners of the cestode \u003cem\u003elysosomal alpha-glucosidase\u003c/em\u003e, we not only identified its presence but also demonstrated a correlation between their expressions using a linear model (p\u0026thinsp;=\u0026thinsp;0.03, r\u0026thinsp;=\u0026thinsp;0.113; Fig. S2). Analysis of GO terms enriched in the list of the correlation partners of \u003cem\u003elysosomal alpha-glucosidase\u003c/em\u003e revealed the term \u003cem\u003eregulation of cellular protein metabolic process\u003c/em\u003e (GO:0032268; table S2) with 174 genes. This metabolic pathway is intertwined with glucose metabolism and glycolysis [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. We find further connection to glucose metabolism with the term \u003cem\u003eresponse to osmotic stress\u003c/em\u003e (GO:0006970; 12 genes), which can be linked to altered glucose concentrations [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Alpha-glucosidases can also influence neuromuscular functions and a deficiency can cause motor and respiratory disorders, known as Pompe disease in vertebrates [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Therefore, unsurprisingly, the most common GO term is \u003cem\u003eneuron projection development\u003c/em\u003e (GO:0031175) with 106 genes. Pompe disease decreases glycogen concentration in projection neurons [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Additionally, we identified a GO term associated with cuticle development, specifically the \u003cem\u003echitin-based embryonic cuticle biosynthetic process\u003c/em\u003e (GO:0008362). This may be relevant, as chitin-containing materials are known to act as inhibitors of \u003cem\u003ealpha-glucosidase\u003c/em\u003e [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e] and infected ants that become infected during the larval stage exhibit a reduced sclerotization and melanisation of the cuticle during the pupal stage.\u003c/p\u003e\u003cp\u003eWe also obtained the GO terms for host correlation partners of six commonly secreted cestode proteins that could not be annotated [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Four of these genes were located in the dark orange module, representing the second, third, twelfth, and thirteenth most abundant parasitic proteins in the ant haemolymph, while two were in the turquoise module, corresponding to the fourth and sixth most abundant proteins (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ef). The second most abundant gene had 97 correlation partners and was associated with three significant GO terms, all based on two genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ef). One of these terms is \u003cem\u003eSMAD protein signal transduction\u003c/em\u003e (GO:0060395; for a statistics overview of all significant GO terms of unannotated genes, see table S3), a signalling pathway involved in muscle hypertrophy and the negative regulation of muscle growth [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. This term co-occurs with \u003cem\u003epositive regulation of cardiac muscle hypertrophy\u003c/em\u003e (GO:0010613). Further examination of other candidates in the dark orange module revealed that these cestode genes also strongly interact with genes involved in the SMAD signalling pathway (\u003cem\u003eSMAD protein signal transduction\u003c/em\u003e, GO:0060395; 13th most abundant protein; table S3) and other muscle-related functions, including \u003cem\u003eneuromuscular process controlling posture\u003c/em\u003e (GO:0050884), \u003cem\u003epositive regulation of cardiac muscle hypertrophy\u003c/em\u003e (GO:0010613), and \u003cem\u003eadult walking behaviour\u003c/em\u003e (GO:0007628; 12th most abundant protein; table S3). Given that infected ants exhibit symptoms of muscular dystrophy [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] and are much less active [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], these interactions may provide insight into the molecular mechanisms underlying the observed muscle dysfunction. We also identified two immune-related functions among these interacting host genes, including the \u003cem\u003emelanin biosynthetic process\u003c/em\u003e (GO:0042438), which plays a critical role in the encapsulation of foreign substances [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e] and \u003cem\u003enegative regulation of lamellocyte differentiation\u003c/em\u003e (GO:0035204), lamellocytes being key insect immune cells [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. We detected a high degree of coherence in the GO terms among the correlation partners of the fourth and sixth most abundant cestode proteins in the ant haemolymph, both of which are part of the turquoise module. These proteins interact with host genes enriched for \u003cem\u003etyrosine catabolic process\u003c/em\u003e (GO:0006572) and \u003cem\u003eL-phenylalanine catabolic process\u003c/em\u003e (GO:0006559). Notably, the tyrosine pathway is involved in sclerotization and melanisation of the insect cuticle [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e], another GO term of which can be found in \u003cem\u003ecuticle hydrocarbon biosynthetic process\u003c/em\u003e (GO:0006723) interacting with the fourth most expressed gene. Moreover, phenylalanine catabolism plays a crucial role in the encapsulation of malaria parasites in mosquitoes. When phenylalanine catabolism is disrupted, for example, through the silencing of phenylalanine hydroxylase, this encapsulation process is impaired [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e] and mosquitoes became unable to encapsulate malaria parasites [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. The expression of the fourth most abundant protein is associated with host genes involved in lipogenesis, for which we identified nine enriched GO terms (GO:0010873, GO:0043651, GO:1903966, GO:0035338, GO:0036109, GO:0034625, GO:0034626, GO:0019367 and GO:0019367; table S3).\u003c/p\u003e\u003cp\u003eConsidering that the fat body is the most important immune organ in insects [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e], fat metabolism and immunity are likely closely interconnected. While our GO analysis did not identify specific immune functions beyond \u003cem\u003eL-phenylalanine catabolic process\u003c/em\u003e (GO:0006559) and the \u003cem\u003eresponse to cobalt ion\u003c/em\u003e (GO:0032025) involved in detoxification, the involvement of genes in lipogenesis may provide insights into how the immune system of infected ants is altered. For instance, in \u003cem\u003eDrosophila\u003c/em\u003e lipogenesis is suppressed by the Toll signalling pathway during periods of immune stress [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e], and lipids themselves can play a role in the immune responses against fungal parasites [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e].\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThrough our novel application of the Weighted Gene Co-expression Network Analysis (WGCNA) in a joint dataset of individual host and parasite transcriptomes, we have gained significant insights into how host and parasite transcriptional activities are intertwined. Our findings reveal that the expression of cestode genes is linked to a substantially greater number of genes compared to host genes. In six modules, ant genes were more likely to correlate with cestode genes than with other host genes. Notably, within these modules, cestode genes primarily interacted with other cestode genes. This pattern appears to be achieved via a reduction in the linkage of ant gene expression to other genes, contrasting with the extensive connectivity observed among cestode genes.\u003c/p\u003e\u003cp\u003eThis effect is particularly evident in the hub genes of these modules. In modules where ant genes correlated more frequently with cestode genes, the representation of hub genes was overwhelmingly dominated by cestode genes. One plausible explanation is that \u003cem\u003eA. brevis\u003c/em\u003e has evolved to exploit the molecular physiology of \u003cem\u003eT. nylanderi\u003c/em\u003e, with a substantial proportion of the parasite's expressed genes interacting with host genes. By contrast, \u003cem\u003eT. nylanderi\u003c/em\u003e interacts not only with the cestode but also with nestmates and the broader biotic and abiotic environment, so that its transcriptionally activity is less shaped by its parasite.\u003c/p\u003e\u003cp\u003eFor instance, consider a scenario where the host is challenged by a pathogenic infection. To combat the threat, the host must activate its immune system, altering gene expression in the fat body. Such activation is likely to have minimal effects on the rest of the host's gene expression. For the cestode, on the other hand, a host immune challenge may necessitate activating its own immune defences to prevent hyperparasitism, leading to significant shifts in its gene expression [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e], to regulate the host\u0026rsquo;s immune system upon immune challenge [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e] and adapt to a possibly more hostile environment caused by the immune response [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. This would mean the co-expression between the parasite\u0026rsquo;s stress responses, immune system, parasite-host communication with only the host\u0026rsquo;s immune system. When considering the scenario where the parasite directly influences the host gene expression, the parasite would be more likely to benefit from fewer changes, thus the parasite might even take the burden of gene expression change compared to the host.\u003c/p\u003e\u003cp\u003eBesides the larger gene expression patterns in parasite and host, we demonstrated the correlation partners of genes whose proteins are commonly secreted into the ant haemolymph. For the annotated genes, we observed that their functions were closely associated with biological processes in the ant that were either analogous to, or likely influenced by, the functions of these genes in parasites. First, we highlight the oxidative stress genes \u003cem\u003esuperoxide dismutase\u003c/em\u003e and \u003cem\u003ethioredoxin peroxidase\u003c/em\u003e. Our analysis revealed highly interactive expression between these two genes. They were clustered within the same module, with \u003cem\u003esuperoxide dismutase\u003c/em\u003e correlating with all but one of the genes that \u003cem\u003ethioredoxin peroxidase\u003c/em\u003e also interacted with. This finding aligns with previous studies, which have shown that \u003cem\u003esuperoxide dismutase\u003c/em\u003e and \u003cem\u003ethioredoxin peroxidase\u003c/em\u003e function within the same oxidative stress pathway in systems without parasite involvement [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e] and in parasitic cestodes [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. The genes they correlate with indicate that their primary role is not necessarily in direct communication with the host but rather in defence against the oxidative stress generated by the host. It has been hypothesized that \u003cem\u003ethioredoxin peroxidase\u003c/em\u003e, in particular, is secreted by parasites into the host primarily to modulate oxidative stress, which arises naturally in the host through aerobic metabolism [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. This conclusion is supported by the observation that the associated gene functions are primarily involved in metabolism and correlate with other genes that mitigate oxidative stress in the host. It is plausible that this modulation of oxidative stress contributes to the significantly extended lifespan of the host. However, the high level of secretion of these proteins may not have originally evolved for this purpose, as these genes are among the most frequently expressed in many parasite-host systems [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. Thus, their contribution to lifespan extension could be an incidental by-product rather than an adaptive trait. What becomes evident from the presence of \u003cem\u003ethioredoxin peroxidase\u003c/em\u003e is that \u003cem\u003eA. brevis\u003c/em\u003e seems to be able to thrive in its cysticercoid stage in an aerobic environment within the host. This ability is notable, as Platyhelminthes are known to adapt to anaerobic environments at various life stages [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. For \u003cem\u003edisulfide isomerase\u003c/em\u003e, we found that its correlation partners are predominantly linked to secretion, consistent with the established functions of disulfide isomerases in parasites and other systems [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. The last annotated gene, \u003cem\u003ealpha-glucosidase\u003c/em\u003e, also supports this interpretation. Similar to previous findings with \u003cem\u003ebeta-glucosidase\u003c/em\u003e [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e], we observed a negative correlation between parasite \u003cem\u003ealpha-glucosidase\u003c/em\u003e and host \u003cem\u003ealpha-glucosidase\u003c/em\u003e. Additionally, its correlation partners are associated with glucose metabolism. \u003cem\u003eAlpha-glucosidases\u003c/em\u003e are enzymes that catalyse the breakdown of polymeric glucose variants, such as starch or glycogen, into glucose monomers (63). This gene is thus a strong candidate for involvement in the cestode's nutrient acquisition, as glucose uptake is critical for cestode survival and growth [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e]. This activity contrasts with the expected reduction of glycogen levels in infected hosts. Interestingly, metacestode-infected beetles have been reported to exhibit increased glycogen levels (65), potentially as a compensatory response to maintain stable glycogen reserves in the presence of cestode \u003cem\u003ealpha-glucosidase\u003c/em\u003e. This interplay highlights the intricate metabolic interactions between host and parasite.\u003c/p\u003e\u003cp\u003eFinally, we discuss the functions of host genes whose expression is associated with as-yet unannotated proteins secreted into the ant's haemolymph. The four genes in the dark orange module may play a role in manipulating the host's behaviour and morphology. Among the host genes associated with these proteins, we identified functions related to muscle development and the SMAD signalling pathway. This suggests that these cestode genes could influence the host's muscle development, potentially contributing to observed changes in host behaviour and morphology [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Although \u003cem\u003eA. brevis\u003c/em\u003e has never been found in the host\u0026rsquo;s brain, there have been reports on parasites whose infection causes behavioural alterations in social insects while not being present in the brain [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e]. This would additionally explain the presence of the GO term of walking behaviour. Given these clues we believe these genes to be strong candidates for involvement the host\u0026rsquo;s sluggish behaviour and we believe the high abundance of their protein products in the haemolymph might serve as a clue for the fact that these proteins need to travel all the way to the host\u0026rsquo;s brain.\u003c/p\u003e\u003cp\u003eAdditionally, the two cestode genes identified in the turquoise module appear to play a role in suppressing the immune response, potentially with the side effect of inhibiting cuticle sclerotization. This hypothesis is supported by the identification of numerous genes associated with lipogenesis and direct immune functions in this module. Alternatively, this suppression could represent a response to the host\u0026rsquo;s immune activity or rather the suppression of the host\u0026rsquo;s immune system, which cestodes are known to be able to do [\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e]. Due to this study being limited on the fact that correlation does not mean causation we propose that future experiments focus on this pathway in the host. In adult ants, the silencing of these genes might re-activate the immune response towards the parasite, leading to the possible overexpression of serine proteases, which are involved in immune avoidance in cestodes [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e] and has been shown to be affected by parasite load in this system [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Finally, the expression of these genes should also be tested in cestode-infected larvae to test whether these genes in any way correlate to ant genes that are involved in the melanisation of the cuticle. This way it would be possible to link parasite immune suppression to a key phenotypic trait of infected ants [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn summary, our analysis demonstrates a remarkable integration of the parasite's transcriptome into the host's, with the high connectivity of parasite genes indicating a sustained, active correlation between the two and cestode genes being present in every single module. Through our novel application of WGCNA, we identified numerous candidate genes with previously unknown functions, while known candidate genes aligned well with findings from other studies. These results highlight the effectiveness of this approach in elucidating the interactome between parasite and host, particularly in non-model organisms.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eWGCNA \u0026ndash; Weighted Gene Co-Expression Network Analysis, GO \u0026ndash; Gene Ontology, BLAST -Basic Local Alignment Search Tool, KEGG \u0026ndash; Kyoto Encyclopedia for Genes and Genomes, TOM plot \u0026ndash; Topological Overlap Matrix plot.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to publish\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no competing interests\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis project was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)—GRK2526/1—Project no. 407023052.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eConceptualization T.S. and S.F.. Transcriptome analysis T.S. with consultation of R.L.. Original draft writing T.S. with revision comments from R.L and S.F.. Funding S.F.\u003c/p\u003e\n\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eWe obtained our data from the published dataset of Sistermans et al. (2025; methodological details see supplement[13]), the raw reads of which can be found on the SRA database of NCBI (PRJNA1246159), and the gene count matrices, GO terms and KEGG terms on Dryad (DOI: 10.5061/dryad.8cz8w9h3b).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eEvans HC, Elliot SL, Hughes DP. Ophiocordyceps unilateralis. 2011;4:598\u0026ndash;602. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/0.1371/journal.pone\u003c/span\u003e\u003cspan address=\"https://doi.org/0.1371/journal.pone\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWeinersmith K, Faulkes Z. Parasitic manipulation of hosts\u0026rsquo; phenotype, or how to make a zombie - An introduction to the symposium. Integrative and Comparative Biology. 2014;54:93\u0026ndash;100. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/icb/icu028\u003c/span\u003e\u003cspan address=\"10.1093/icb/icu028\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eH\u0026oslash;eg JT. The biology and life cycle of the Rhizocephala (Cirripedia). Journal of the Marine Biological Association of the United Kingdom. 1995;75:517\u0026ndash;50. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1017/S0025315400038996\u003c/span\u003e\u003cspan address=\"10.1017/S0025315400038996\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTobias ZJC, Fowler AE, Blakeslee AMH, Darling JA, Torchin ME, Miller AW, et al. Invasion history shapes host transcriptomic response to a body-snatching parasite. Mol Ecol. 2021;30:4321\u0026ndash;37. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/mec.16038\u003c/span\u003e\u003cspan address=\"10.1111/mec.16038\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVuitton DA. The ambiguous role of immunity in echinococcosis: protection of the host or of the parasite? Acta Trop. 2003;85:119\u0026ndash;32.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePoulin R, Maure F. Host Manipulation by Parasites: A Look Back Before Moving Forward. Trends Parasitol. 2015;31:563\u0026ndash;70. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.pt.2015.07.002\u003c/span\u003e\u003cspan address=\"10.1016/j.pt.2015.07.002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eC\u0026eacute;zilly F, Thomas F, M\u0026eacute;doc V, Perrot-Minnot MJ. Host-manipulation by parasites with complex life cycles: adaptive or not? Trends Parasitol. 2010;26:311\u0026ndash;7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.pt.2010.03.009\u003c/span\u003e\u003cspan address=\"10.1016/j.pt.2010.03.009\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePoulin R, Brodeur J, Moore J. Parasite Manipulation of Host Behaviour: Should Hosts Always Lose? Oikos. 1994;70:479\u0026ndash;84.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBeros S, Jongepier E, Hagemeier F, Foitzik S. The parasite\u0026rsquo;s long arm: A tapeworm parasite induces behavioural changes in uninfected group members of its social host. Proceedings of the Royal Society B: Biological Sciences. 2015;282. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1098/rspb.2015.1473\u003c/span\u003e\u003cspan address=\"10.1098/rspb.2015.1473\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFeldmeyer B, Mazur J, Beros S, Lerp H, Binder H, Foitzik S. Gene expression patterns underlying parasite-induced alterations in host behaviour and life history. Mol Ecol. 2016;25:648\u0026ndash;60. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/mec.13498\u003c/span\u003e\u003cspan address=\"10.1111/mec.13498\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBeros S, Lenhart A, Scharf I, Negroni MA, Menzel F, Foitzik S. Extreme lifespan extension in tapeworm-infected ant workers. Royal Soc Open Sci. 2021;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1098/rsos.202118\u003c/span\u003e\u003cspan address=\"10.1098/rsos.202118\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTrabalon M, Plateaux L, P\u0026eacute;ru L, Bagn\u0026egrave;res AG, Hartmann N. Modification of morphological characters and cuticular compounds in worker ants Leptothorax nylanderi induced by endoparasites Anomotaenia brevis. J Insect Physiol. 2000;46:169\u0026ndash;78. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S0022-1910(99)00113-4\u003c/span\u003e\u003cspan address=\"10.1016/S0022-1910(99)00113-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSistermans T, Darras H, Rognet V, Beros S, Hartke J, Stoldt M, et al. Parasite prevalence in a social host has colony-wide impacts on transcriptional activity and survival. Evolution. 2025;qpaf118. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/evolut/qpaf118\u003c/span\u003e\u003cspan address=\"10.1093/evolut/qpaf118\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDavis FP, Barkan DT, Eswar N, Mckerrow JH, Sali A. Host \u0026ndash; pathogen protein interactions predicted by comparative modeling. Protein Sci. 2009. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1110/ps.073228407.6\u003c/span\u003e\u003cspan address=\"10.1110/ps.073228407.6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDyer MD, Murali TM, Sobral BW. Computational prediction of host-pathogen protein \u0026ndash; protein interactions. Bioinformatics. 2007. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/bioinformatics/btm208\u003c/span\u003e\u003cspan address=\"10.1093/bioinformatics/btm208\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSoyemi J, Isewon I, Oyelade J, Adebiyi E. Inter-Species/Host-Parasite Protein Interaction Predictions Reviewed. 2018;:396\u0026ndash;406. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.2174/1574893613666180108155851\u003c/span\u003e\u003cspan address=\"10.2174/1574893613666180108155851\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJackson AP. Genome evolution in trypanosomatid parasites. Parasitology. 2015;142:S40\u0026ndash;56. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1017/S0031182014000894\u003c/span\u003e\u003cspan address=\"10.1017/S0031182014000894\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePan G, Xu J, Li T, Xia Q, Liu S-L, Zhang G, et al. Comparative genomics of parasitic silkworm microsporidia reveal an association between genome expansion and host adaptation. BMC Genomics. 2013;14:186. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/1471-2164-14-186\u003c/span\u003e\u003cspan address=\"10.1186/1471-2164-14-186\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLynch VJ. Inventing an arsenal: adaptive evolution and neofunctionalization of snake venom phospholipase A2 genes. BMC Evol Biol. 2007;7:2. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/1471-2148-7-2\u003c/span\u003e\u003cspan address=\"10.1186/1471-2148-7-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSistermans T, Hartke J, Stoldt M, Libbrecht R, Foitzik S. The influence of parasite load on transcriptional activity and morphology of a cestode and its ant intermediate host. Mol Ecol. 2023;4412\u0026ndash;26. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/mec.16995\u003c/span\u003e\u003cspan address=\"10.1111/mec.16995\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eStoldt M, Klein L, Beros S, Butter F, Jongepier E, Feldmeyer B, et al. Parasite presence induces gene expression changes in an ant host related to immunity and longevity. Genes. 2021;12. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/genes12010095\u003c/span\u003e\u003cspan address=\"10.3390/genes12010095\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHartke J, Ceron-Noriega A, Stoldt M, Sistermans T, Kever M, Fuchs J, et al. Long live the host ! Proteomic analysis reveals possible strategies for parasitic manipulation of its social host. Mol Ecol. 2023;32:5877\u0026ndash;89. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/mec.17155\u003c/span\u003e\u003cspan address=\"10.1111/mec.17155\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eArrese EL, Soulages JL. Insect fat body: Energy, metabolism, and regulation. Ann Rev Entomol. 2010;55:207\u0026ndash;25. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1146/annurev-ento-112408-085356\u003c/span\u003e\u003cspan address=\"10.1146/annurev-ento-112408-085356\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLangfelder P, Horvath S. WGCNA: An R package for weighted correlation network analysis. BMC Bioinformatics. 2008. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/1471-2105-9-559\u003c/span\u003e\u003cspan address=\"10.1186/1471-2105-9-559\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. 9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, et al. Cytoscape: A Software Environment for Integrated Models. Genome Res. 2003;13:426. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1101/gr.1239303.metabolite\u003c/span\u003e\u003cspan address=\"10.1101/gr.1239303.metabolite\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHaas BJ, Papanicolaou A, Yassour M, Grabherr M, Blood PD, Bowden J, et al. De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis. Nat Protoc. 2013;8:1494\u0026ndash;512. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/nprot.2013.084\u003c/span\u003e\u003cspan address=\"10.1038/nprot.2013.084\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDow JAT. The essential roles of metal ions in insect homeostasis and physiology. Curr Opin Insect Sci. 2017;23:43\u0026ndash;50. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.cois.2017.07.001\u003c/span\u003e\u003cspan address=\"10.1016/j.cois.2017.07.001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePowers SK, Ji LL, Kavazis AN, Jackson MJ. Reactive oxygen species: impact on skeletal muscle. Compr Physiol. 2011;1:941\u0026ndash;69. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/cphy.c100054.REACTIVE\u003c/span\u003e\u003cspan address=\"10.1002/cphy.c100054.REACTIVE\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYang W, Li J, Hekimi S. A measurable increase in oxidative damage due to reduction in superoxide detoxification fails to shorten the life span of long-lived mitochondrial mutants of Caenorhabditis elegans. Genetics. 2007;177:2063\u0026ndash;74. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1534/genetics.107.080788\u003c/span\u003e\u003cspan address=\"10.1534/genetics.107.080788\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNegroni MA, Foitzik S, Feldmeyer B. Long-lived Temnothorax ant queens switch from investment in immunity to antioxidant production with age. Sci Rep. 2019;9:1\u0026ndash;10. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41598-019-43796-1\u003c/span\u003e\u003cspan address=\"10.1038/s41598-019-43796-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eParker JD, Parker KM, Sohal BH, Sohal RS. Decreased expression of Cu-Zn superoxide dismutase 1 in ants with extreme lifespan. Proc Natl Acad Sci USA. 2004;101:3486\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1073/pnas.0400222101\u003c/span\u003e\u003cspan address=\"10.1073/pnas.0400222101\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTasaki E, Kobayashi K, Matsuura K, Iuchi Y. Long-Lived Termite Queens Exhibit High Cu/Zn-Superoxide Dismutase Activity. Hindawi. 2018.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCalvani END, De Marco Verissimo C, Jewhurst HL, Cwiklinski K, Flaus A, Dalton JP. Two Distinct Superoxidase Dismutases (SOD) Secreted by the Helminth Parasite Fasciola hepatica Play Roles in Defence against Metabolic and Host Immune Cell-Derived Reactive Oxygen Species (ROS) during Growth and Development. Antioxidants. 2022;11:1\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMcGonigle S, Curley GP, Dalton JP. Cloning of peroxiredoxin, a novel antioxidant enzyme, from the helminth parasite Fasciola hepatica. Parasitology. 1997;115:101\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSalinas G, Fernandez V, Fernandez C, Selkirk ME. Echinococcus granulosus: Cloning of a Thioredoxin Peroxidase. Exp Parasitol. 1998;90:298\u0026ndash;301.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSokolova N, Pan S, Provazza S, Beutner G, Vendelin M, Birkedal R. ADP Protects Cardiac Mitochondria under Severe Oxidative Stress. PLoS ONE. 2013. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone.0083214\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0083214\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. 8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAchour YB, Chenik M, Louzir H, Dellagi K. Identification of a Disulfide Isomerase Protein of Leishmania major as a Putative Virulence Factor. Fungal and parasitic infections. 2002;70:3576\u0026ndash;85. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1128/IAI.70.7.3576\u003c/span\u003e\u003cspan address=\"10.1128/IAI.70.7.3576\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHabash SS, Miroslaw S, Siddique S, Voigt B, Elashry A, Grundler FWM. Identification and characterization of a putative protein disulfide isomerase (HsPDI) as an alleged effector of Heterodera schachtii. Sci Rep. 2017;7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41598-017-13418-9\u003c/span\u003e\u003cspan address=\"10.1038/s41598-017-13418-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTokuhiro K, Ikawa M, Benham AM, Okabe M. Protein disul fi de isomerase homolog PDILT is required for quality control of sperm membrane protein ADAM3 and male fertility. Proc Natl Acad Sci USA. 2012;109:3850\u0026ndash;5. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1073/pnas.1117963109\u003c/span\u003e\u003cspan address=\"10.1073/pnas.1117963109\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eInan M, Aryasomayajula D, Sinha J, Meagher MM. Enhancement of Protein Secretion in Pichia pastoris by Overexpression of Protein Disulfide Isomerase. Biotechnol Bioeng. 2006;93:771\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/bit.20762\u003c/span\u003e\u003cspan address=\"10.1002/bit.20762\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBaker PF, Knight DE. Exocytosis: control by calcium and other factors. Br Med Bull. 1986;42:399\u0026ndash;404.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHermans MMP, Kroos MA, Van Beeumen J, Oostra BA, Reuser AJJ. Human lysosomal α-glucosidase: Characterization of the catalytic site. J Biol Chem. 1991;266:13507\u0026ndash;12. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/s0021-9258(18)92727-4\u003c/span\u003e\u003cspan address=\"10.1016/s0021-9258(18)92727-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVysotskaya RU, Krupnova MY, Ieshko EP, Anikieva LV, Lebedeva DI. Ecological and biochemical aspects of parasite-host interactions in transformed aquatic bodies: A case study of the cestode Triaenophorus nodulosus and its host, the northern pike Esox lucius. Biology Bull. 2015;42:246\u0026ndash;53. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1134/S1062359015030140\u003c/span\u003e\u003cspan address=\"10.1134/S1062359015030140\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCarthew RW. Gene Regulation and Cellular Metabolism: An Essential Partnership. Trends Genet. 2022;37:389\u0026ndash;400. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.tig.2020.09.018.Gene\u003c/span\u003e\u003cspan address=\"10.1016/j.tig.2020.09.018.Gene\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAlbertyn J, Hohmann S, Prior BA. Characterization of the osmotic-stress response in Saccharomyces cerevisiae: osmotic stress and glucose repression regulate glycerol-3-phosphate dehydrogenase independently. Curr Genet. 1994;25:12\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eColella P, Sellier P, Gomez MJ, Biferi MG, Tanniou G, Guerchet N, et al. Gene therapy with secreted acid alpha-glucosidase rescues Pompe disease in a novel mouse model with early-onset spinal cord and respiratory defects. EBioMedicine. 2020;61. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ebiom.2020.103052\u003c/span\u003e\u003cspan address=\"10.1016/j.ebiom.2020.103052\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSidman RL, Taksir T, Fidler J, Zhao M, James C, Passini MA, et al. Temporal Neuropathological and Behavioral Phenotype of 6neo/6neo Pompe Disease Mice. J Neuropathol Exp Neurol. 2009;67:803\u0026ndash;18. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1097/NEN.0b013e3181815994.Temporal\u003c/span\u003e\u003cspan address=\"10.1097/NEN.0b013e3181815994.Temporal\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNguyen VB, Wang S-L. Reclamation of Marine Chitinous Materials for the Production of α -Glucosidase Inhibitors via. Mar Drugs. 2017;15. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/md15110350\u003c/span\u003e\u003cspan address=\"10.3390/md15110350\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNikooie R, Jafari-Sardoie S, Sheibani V, Chatroudi AN. Resistance training - induced muscle hypertrophy is mediated by TGF‐β 1‐Smad signaling pathway in male Wistar rats. J Cell Physiol. 2020;235:5649\u0026ndash;65. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/jcp.29497\u003c/span\u003e\u003cspan address=\"10.1002/jcp.29497\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGillespie JP, Kanost MR, Trenczek T. Biological mediators of insect immunity. Ann Rev Entomol. 1997;42:661\u0026ndash;643.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLavine MD, Strand MR. Insect hemocytes and their role in immunity. Insect Biochem Mol Biol. 2002;32:1295\u0026ndash;309.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiu C, Yamamoto K, Cheng T-C, Kadono-Okuda K, Narukawa J, Liu S-P, et al. Repression of tyrosine hydroxylase is responsible for the sex-linked chocolate mutation of the silkworm, Bombyx mori. Proc Natl Acad Sci U S A. 2010;107:12980\u0026ndash;5. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1073/pnas.1001725107\u003c/span\u003e\u003cspan address=\"10.1073/pnas.1001725107\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCalvo AC, Pey AL, Ying M, Loer CM, Martinez A. Anabolic function of phenylalanine hydroxylase in Caenorhabditis elegans. FASEB J. 2008;22:2601\u0026ndash;3096. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1096/fj.08-108522\u003c/span\u003e\u003cspan address=\"10.1096/fj.08-108522\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFuchs S, Behrends V, Bundy JG, Crisanti A, Nolan T. Phenylalanine Metabolism Regulates Reproduction and Parasite Melanization in the Malaria Mosquito. PLoS ONE. 2014;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone.0084865\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0084865\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHoffmann JA, Reichhart J. Drosophila innate immunity: an evolutionary perspective. Nat Immunol. 2002;3:121\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDiangelo JR, Bland ML, Bambina S, Cherry S, Birnbaum MJ. The immune response attenuates growth and nutrient storage in Drosophila by reducing insulin signaling. Proc Natl Acad Sci USA. 2009;106:20853\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1073/pnas.0906749106\u003c/span\u003e\u003cspan address=\"10.1073/pnas.0906749106\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWronska AK, Kaczmarek A, Bogus MI, Kuna A. Lipids as a key element of insect defense systems. Front Genet. 2023;14. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fgene.2023.1183659\u003c/span\u003e\u003cspan address=\"10.3389/fgene.2023.1183659\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eParratt SR, Laine AL. Pathogen dynamics under both bottom-up host resistance and top-down hyperparasite attack. J Appl Ecol. 2018;55:2976\u0026ndash;85. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/1365-2664.13185\u003c/span\u003e\u003cspan address=\"10.1111/1365-2664.13185\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePirovino M, Iseli C, Curran JA, Conrad B. Birth of immunity in early life: stepwise emergence of resistance and immunity to complex molecular parasites via progressively degenerating hyperparasites. bioRxiv. 2023.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHernandez JLR, Leung G, McKay DM. Cestode regulation of inflammation and inflammatory diseases. Int J Parasitol. 2013;43:233\u0026ndash;43. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ijpara.2012.09.005\u003c/span\u003e\u003cspan address=\"10.1016/j.ijpara.2012.09.005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMideo N. Parasite adaptations to within-host competition. Evolutionary Parasitol. 2009;25:261\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.pt.2009.03.001\u003c/span\u003e\u003cspan address=\"10.1016/j.pt.2009.03.001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePedrajas JR, Carreras A, Valderrama R, Barroso JB. Mitochondrial 1-Cys-peroxiredoxin/thioredoxin system protects manganese-containing superoxide dismutase (Mn-SOD) against inactivation by peroxynitrite in Saccharomyces cerevisiae. Nitric Oxide - Biology Chem. 2010;23:206\u0026ndash;13. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.niox.2010.06.004\u003c/span\u003e\u003cspan address=\"10.1016/j.niox.2010.06.004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHalliwell B, Gutteridge JMC. Free Radicals in Biology and Medicine. Oxford: Oxford University Press; 1989.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChehayeb JF, Robertson AP, Martin RJ, Geary TG. Proteomic Analysis of Adult Ascaris suum Fluid Compartments and Secretory Products. PLoS Negl Trop Dis. 2014;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pntd.0002939\u003c/span\u003e\u003cspan address=\"10.1371/journal.pntd.0002939\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMart\u0026iacute;nez-Gonz\u0026aacute;lez J, de Guevara-Flores J, Del Arenal Mena A. Evolutionary Adaptations of Parasitic Flatworms to Different Oxygen Tensions. Antioxidants. 2022;11. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/antiox11061102\u003c/span\u003e\u003cspan address=\"10.3390/antiox11061102\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNaguleswaran A, Alaeddine F, Guionaud C, Vonlaufen N, Sonda S, Jenoe P, et al. Neospora caninum protein disulfide isomerase is involved in tachyzoite-host cell interaction. Int J Parasitol. 2005;35:1459\u0026ndash;72. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ijpara.2005.06.006\u003c/span\u003e\u003cspan address=\"10.1016/j.ijpara.2005.06.006\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eStolf BS, Smyrnias I, Lopes LR, Vendramin A, Goto H, Laurindo FRM, et al. Protein disulfide isomerase and host-pathogen interaction. TheScientificWorldJournal. 2011;11:1749\u0026ndash;61. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1100/2011/289182\u003c/span\u003e\u003cspan address=\"10.1100/2011/289182\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKashiide T, Kikuta S, Yamaguchi M, Irie T, Kouguchi H, Yagi K, et al. Molecular and functional characterization of glucose transporter genes of the fox tapeworm Echinococcus multilocularis. Mol Biochem Parasitol. 2018;225:7\u0026ndash;14. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.molbiopara.2018.08.004\u003c/span\u003e\u003cspan address=\"10.1016/j.molbiopara.2018.08.004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBeani L. Crazy wasps: when parasites manipulate the Polistes phenotype. Ann Zool Fenn. 2006;43:564\u0026ndash;74.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHughes DP, Kathirithamby J, Turillazzi S, Beani L. Social wasps desert the colony and aggregate outside if parasitized: parasite manipulation? Behav Ecol. 2004;15:1037\u0026ndash;43. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/beheco/arh111\u003c/span\u003e\u003cspan address=\"10.1093/beheco/arh111\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVendelova E, Lutz MB, Hrčkov\u0026aacute; G. Immunity and immune modulation elicited by the larval cestode Mesocestoides vogae and its products. Parasite Immunol. 2015;37:493\u0026ndash;504. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/pim.12216\u003c/span\u003e\u003cspan address=\"10.1111/pim.12216\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eIzvekova GI, Frolova TV. Proteolytic enzymes and their inhibitors in cestodes. Biology Bull Reviews. 2017;7:150\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1134/s2079086417020049\u003c/span\u003e\u003cspan address=\"10.1134/s2079086417020049\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePatel S. A critical review on serine protease: Key immune manipulator and pathology mediator. Allergol Immunopathol. 2017;45:579\u0026ndash;91. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.aller.2016.10.011\u003c/span\u003e\u003cspan address=\"10.1016/j.aller.2016.10.011\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJongepier E, S\u0026eacute;guret A, Labutin A, Feldmeyer B, Gst\u0026ouml;ttl C, Foitzik S, et al. Convergent Loss of Chemoreceptors across Independent Origins of Slave-Making in Ants. Mol Biol Evol. 2022;39. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/molbev/msab305\u003c/span\u003e\u003cspan address=\"10.1093/molbev/msab305\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, et al. Seq Anal. 2013;29:15\u0026ndash;21. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/bioinformatics/bts635\u003c/span\u003e\u003cspan address=\"10.1093/bioinformatics/bts635\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZanini F, Anders S, Pyl PT, Pimanda JE. Gene expression Analysing high-throughput sequencing data in Python with HTSeq 2. 0. 2022;38 March:2943\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWingett SW, Andrews S. Fastq screen: A tool for multi-genome mapping and quality control [version 1; referees: 3 approved, 1 approved with reservations]. F1000Research. 2018;7 May:1\u0026ndash;13. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.12688/f1000research.15931.1\u003c/span\u003e\u003cspan address=\"10.12688/f1000research.15931.1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChen S, Zhou Y, Chen Y, Gu J, Fastp. An ultra-fast all-in-one FASTQ preprocessor. Bioinformatics. 2018;34:i884\u0026ndash;90. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/bioinformatics/bty560\u003c/span\u003e\u003cspan address=\"10.1093/bioinformatics/bty560\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKim D, Langmead B, Salzberg SL. HISAT: A fast spliced aligner with low memory requirements. Nat Methods. 2015;12:357\u0026ndash;60. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/nmeth.3317\u003c/span\u003e\u003cspan address=\"10.1038/nmeth.3317\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePertea M, Pertea GM, Antonescu CM, Chang TC, Mendell JT, Salzberg SL. StringTie enables improved reconstruction of a transcriptome from RNA-seq reads. Nat Biotechnol. 2015;33:290\u0026ndash;5. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/nbt.3122\u003c/span\u003e\u003cspan address=\"10.1038/nbt.3122\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBuchfink B, Xie C, Huson DH. Fast and sensitive protein alignment using DIAMOND. Nat Methods. 2014;12:59\u0026ndash;63. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/nmeth.3176\u003c/span\u003e\u003cspan address=\"10.1038/nmeth.3176\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCantalapiedra CP, Hern̗andez-Plaza A, Letunic I, Bork P, Huerta-Cepas J. eggNOG-mapper v2: Functional Annotation, Orthology Assignments, and Domain Prediction at the Metagenomic Scale. Mol Biol Evol. 2021;38:5825\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/molbev/msab293\u003c/span\u003e\u003cspan address=\"10.1093/molbev/msab293\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gics","sideBox":"Learn more about [BMC Genomics](http://bmcgenomics.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/gics","title":"BMC Genomics","twitterHandle":"#BMCGenomics","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Interactome, WGCNA, gene networks, parasite manipulation, social insects","lastPublishedDoi":"10.21203/rs.3.rs-7789718/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7789718/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eHow parasites and hosts interact at the molecular level is one of the key questions in parasitology. However, due to the diverse consequences of parasite infection on host molecular physiology, it can be challenging to identify pathways that are directly targeted by parasites. This applies in particular to non-model systems such as the interaction between the parasitic tapeworm \u003cem\u003eAnomotaenia brevis\u003c/em\u003eand its intermediate host, the ant \u003cem\u003eTemnothorax nylanderi, \u003c/em\u003ewhose phenotype is strongly altered by the infection. By integrating transcriptome information from hosts and their parasites in a combined weighted gene co-expression network analysis (WGCNA), we identified gene networks and candidate genes critical for this parasite-host interaction. Our analysis revealed tight statistical links between the expression of specific parasite genes and key host molecular pathways. The gene networks and correlations identified are consistent with those playing a major role in model parasite-host systems, a validation of our approach. Finally, we gained first insights into the functions of previously unannotated parasite genes, but which can be considered candidates for host manipulation. The expression of genes encoding proteins secreted by the parasite into the host was associated with host genes involved in oxidative stress resistance, metabolism, muscle function, immunity, and cuticular sclerotization, suggesting that the parasite may modulate these molecular pathways in the host. Our findings advance our understanding of parasite interference and highlight key mechanisms in the evolution of these complex molecular interactions.\u003c/p\u003e","manuscriptTitle":"Integrated Gene Co-Expression Analysis of Host–Parasite Transcriptomes Reveals Mechanisms of Host Modulation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-29 06:42:54","doi":"10.21203/rs.3.rs-7789718/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-19T09:35:23+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-07T14:14:24+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-01T18:10:16+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-01T17:47:37+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-23T18:54:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"13058349998867149098073003009565312048","date":"2025-10-20T12:43:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"306378026066662433607937948307406801874","date":"2025-10-15T12:45:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"319634774920455008978040495440860430286","date":"2025-10-15T03:29:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"56319029448294917008946933671095285026","date":"2025-10-14T22:23:59+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-14T22:20:14+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-14T18:29:33+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-10-14T17:11:51+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-13T15:21:17+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Genomics","date":"2025-10-13T15:17:23+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gics","sideBox":"Learn more about [BMC Genomics](http://bmcgenomics.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/gics","title":"BMC Genomics","twitterHandle":"#BMCGenomics","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"dad08bd4-339c-4d31-a304-852a75793d71","owner":[],"postedDate":"October 29th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-02-02T16:06:14+00:00","versionOfRecord":{"articleIdentity":"rs-7789718","link":"https://doi.org/10.1186/s12864-026-12581-6","journal":{"identity":"bmc-genomics","isVorOnly":false,"title":"BMC Genomics"},"publishedOn":"2026-01-31 15:59:30","publishedOnDateReadable":"January 31st, 2026"},"versionCreatedAt":"2025-10-29 06:42:54","video":"","vorDoi":"10.1186/s12864-026-12581-6","vorDoiUrl":"https://doi.org/10.1186/s12864-026-12581-6","workflowStages":[]},"version":"v1","identity":"rs-7789718","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7789718","identity":"rs-7789718","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}