Subtle transcriptomic response of Eurasian perch (Perca fluvatilis) associated with Triaenophorus nodulosus plerocercoid infection

doi:10.21203/rs.3.rs-3086314/v1

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Subtle transcriptomic response of Eurasian perch (Perca fluvatilis) associated with Triaenophorus nodulosus plerocercoid infection

https://doi.org/10.21203/rs.3.rs-3086314/v1

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Background

Determining the physiological effects of parasites and characterizing genes involved in host responses to infections are essential to improving our understanding of host-parasite interactions and their ecological and evolutionary consequences. This task, however, is complicated by high diversity and complex life histories of many parasite species. The use of transcriptomics in the context of wild-caught specimens can help ameliorate this by providing both qualitative and quantitative information on gene expression patterns in response to parasites in specific host organs and tissues. Here, we evaluated the physiological impact of the widespread parasite, the pike tapeworm (Triaenophorus nodulosus),on its second intermediate host, the Eurasian perch (Perca fluviatilis).

Methods

We used an RNAseq approach to analyse gene expression in the liver, the target organ of T. nodulosus plerocercoids, and spleen which is one of the main immune organs in teleost fishes. We compared perch collected from multiple lakes with individuals with (n = 8) and without (n = 6) T. nodulosus plerocercoids in the liver.

Results

Results revealed a small number of differentially expressed genes (DEGs, adjusted p-value ≤ 0.05) in both spleen (n = 22) and liver (n = 10). DEGs in spleen consisted of mostly upregulated immune related genes (e.g., JUN, SIK1, THSB1), while those in the liver were often linked to metabolic functions (e.g., FABP1, CADM4, CDAB). However, Gene Ontology (GO) analysis showed lack of functional enrichment among DEGs.

Conclusions

This study demonstrates that Eurasian perch displays a subtle response at a gene expression level to T. nodulosus, which together with earlier work, suggests that moderate T. nodulosus plerocercoid infection most likely does not provoke an extensive host immune response and have relatively low physiological costs for the host. Our findings illustrate that not all conspicuous infections have severe effects on host gene regulation.

Triaenophorus nodulosus

parasites

transcriptome

helminth

RNAseq

Platyhelminthes

liver parasites

Mounting an appropriate response to a parasite infection is essential for host’s fitness and survival prospects. The magnitude of such a response, involving immediate immune response, inflammation, or wound repair, is expected to be influenced by many factors, including the parasite, environmental variables, and individual host characteristics [1–3]. The use of next-generation sequencing (NGS) technologies improves our ability to understand the molecular basis of such complex host-parasite interactions, even in the wild [4–6]. For instance, by characterizing tissue-specific gene expression, we can gain novel insights into the genes that are likely involved in the immune responses or tissue repair of the host in response to parasite infection [7–10]. Consequently, this provides targets for future investigation, and even discoveries of potential anti-parasitic drug targets for various ecologically or economically important species [11, 12].

The Eurasian perch (Perca fluviatilis) is a widely distributed freshwater fish species native to Eurasia throughout Europe to Eastern Siberia [13]. It is a generalist feeder and has a rich parasite fauna [14–17] hosting nearly 150 parasite species [13]. Despite a large and increasing body of research on perch biology, ecology, and genetics [18–20], relatively little is known about perch–parasite interactions at a molecular level [20]; however, this situation is slowly changing, at least in part because of growing importance of Eurasian perch in aquaculture [21] and an increasing availability of molecular resources [22–24]. Yet, the ecological relevance of the majority of parasite infections on perch are currently not known, which underlines the need for performing studies outside of a contained laboratory settings [25].

One of the common parasites of Eurasian perch is the pike tapeworm (Triaenophorus nodulosus), a widespread parasitic helminth (Cestoda) which frequently uses P. fluviatilis as a second intermediate host [14] to infect its definitive host, the northern pike (Esox lucius) [26]. Commonly, perch are infected by T. nodulous as fry and juveniles by feeding on infected zooplankton (e.g., Cyclops, Daphnia, Diaptomus, and others [17]). The ingested parasite migrates through the intestine of the perch and punctures the intestinal wall to reach the targeted liver tissue, where it encysts and develops into the plerocercoid phase. The parasite’s migration through tissues can result of the lysis of host membranes, causing inflammation, atrophy, necrosis, and other potentially lethal consequences [13, 14, 27–29]. Damage to the host may be inflicted also at a later infection stage from the increased pressure on the surrounding tissues by large, encapsulated larvae [28]. The severity of T. nodulosus infection was shown to depend on parasite load, so that the condition of the perch deteriorates with increasing parasite numbers (density-dependent effect) [13]. This density-dependent effect has been also observed in pumpkinseeds (Lepomis gibbosus), an invasive teleost in Europe that is often occupying similar niches as the perch [30, 31]. Infection with T. nodulosus in perch has been also associated with a reduction in fertility [4] and ~ 10% reduction in growth rate [13, 14, 17, 31]. However, until now, the physiological effect of T. nodulosus on P. fluviatilis has been studied only using histological techniques and based on a single gene (proliferating cell nuclear antigen) [32]. Thus, despite the potentially severe effect of T. nodulosus infection, we currently lack detailed information on the molecular pathways and processes involved in host responses to the parasite which may be currently attained using whole-transcriptome sequencing.

The aim of this study was to evaluate the response of perch to T. nodulosus infection by comparing the expression profiles of naturally infected and uninfected individuals in two tissues (spleen, liver) at the whole transcriptome level. We hypothesized that (i) responses at the level of transcript abundances will be mild to moderate because of weak physiological effect of plerocercoid infections [4, 13], which enable perch to survive and withstand infection by T. nodulosus plerocercoids for years in natural environment. We also hypothesized that (ii) due to a vital role of liver in haematopoiesis, detoxification and nutritional metabolism, strong transcriptomic response in liver would predominantly reflect the effect of parasite on host condition, feeding and response to physical damage. On the other hand, (iii) given the spleen’s key role in infection response, a high proportion of differentially expressed genes (DEGs) in the spleen would indicate strong immune response of the host.

Fish collection and tissue preparation

In August 2021, fifteen P. fluviatilis individuals were caught using gillnets from four lakes in Estonia. Perch was euthanized with an overdose of benzocaine and measured for weight (± 0.1g) and length (total length; TL, mm) (Table 1). After opening the fish using sterile scalpel, liver and spleen were dissected, snap-frozen on dry ice while in the field and subsequently stored at -80°C. In addition, we recorded the maturation status (mature, immature) and sex of the individual. The national guidelines for the care and use of animals were followed per the Estonian Animal Protection Act, and fishing permits were obtained by the Estonian Ministry of the Environment (no. 10 − 1/21/18).

Table 1

Summary information of analysed *P. fluviatilis* samples and tissues used for this study. Sex (F for female, M for male) and infection status, location, and total length are provided.
Sample ID	Infection status			Lake name	Lake type	Latitude	Longitude	Tissue used	Sex	Total length (mm)
1	Infected			Kasaritsa	Clear	57.781	27.03	Liver	M	126
2	Infected			Kasaritsa	Clear	57.781	27.03	Liver	F	144
3	Infected			Lasa	Humic	57.919	25.789	Liver	M	141
4	Infected			Lasa	Humic	57.919	25.789	Liver, spleen	F	161
5	Uninfected			Lasa	Humic	57.919	25.789	Liver, spleen	M	167
6	Uninfected			Lasa	Humic	57.919	25.789	Liver, spleen	F	163
7	Uninfected			Lasa	Humic	57.919	25.789	Spleen	M	140
8	Infected			Saadjärv	Clear	58.538	26.656	Liver, spleen	F	134
9	Infected			Saadjärv	Clear	58.538	26.656	Spleen	F	129
10	Uninfected			Saadjärv	Clear	58.538	26.656	Liver, spleen	F	103
11	Uninfected			Saadjärv	Clear	58.538	26.656	Liver, spleen	M	103
12	Uninfected			Udriku	Humic	59.296	26.064	Liver	M	152
13	Infected			Udriku	Humic	59.296	26.064	Liver, spleen	F	143
14	Infected			Udriku	Humic	59.296	26.064	Spleen	F	133
15		Uninfected	Lasa		Humic	57.919	25.789	Spleen	M	140

T. nodulosus molecular identification

Infection status was determined by visual identification of plerocercoids in P. fluviatilis livers. Between 2–5 plerocercoids were detected on each infected fish liver (data not shown) and a single plerocercoid was dissected from each of the infected specimens. Plerocercoid samples were fixed in 96% ethanol and stored at -20°C. DNA was extracted from whole plerocercoids using a DNeasy Tissue Kit (Qiagen) according to the manufacturer's instructions. The concentration of isolated DNA was measured with a NanoDrop ND-2000 spectrophotometer (Thermo Scientific). Amplification of the rrnL ribosomal subunit gene [33] was performed in 10 µL reactions to confirm the parasite species T. nodulosus. Each 10 µL polymerase chain reaction (PCR) consisted of 5 µL of 2x Typeit Buffer (Qiagen); 0.5 µL of each primer (500 nM); 2 µL of DNA (100–150 ng total) and 2 µL of nuclease-free water. The primer sequences used for rrnL amplification were following: Cest16SFgen (5’-TRCCTTTTGCATCATG-3’) and Cest_16SRc (5’- AATAGATAAGAACCGACCTGGC-3’) [33]. The thermocycler amplification protocol consisted of initial denaturation at 95°C for 15 min, followed by 40 cycles of 30 s at 94°C, 30 s at 54°C and 90 s at 72°C; the final extension at 72°C was 10 min. Sequencing of PCR product using Sanger method was performed at the Institute of Genomics Core Facility, University of Tartu (Tartu, Estonia) from both directions, and the 22 sequences (forward and reverse) were merged manually. BLAST analysis of 11 consensus sequences indicated that the infecting worms were T. nodulosus (GenBank ID: KR780832.1, highest sequence similarity: 97%). Sequences produced in this study can be accessed at GenBank (OR065063-OR065071).

RNA extraction

Frozen liver tissue samples were mechanically crushed in liquid nitrogen using a steel mortar and pestle to produce a homogenized powder, while frozen spleen tissue was mechanically crushed (the tissue consistency of spleen samples was not conducive to mortar and pestle homogenization) using a Retsch Mixer Mill MM 400 (Retsch). Total RNA was extracted using a NucleoSpin RNA extraction kit (MACHEREY-NAGEL, Duren, Germany). RNA sample concentrations were measured with a NanoDrop 2000 (ThermoFisher), and sample quality was evaluated using a TapeStation 2200 (Agilent Technologies).

Library preparation, sequencing, and quality assessment

Sequencing libraries were prepared at the Novogene Cambridge Science Park (Cambridge, United Kingdom) from 300 ng total RNA. After fragmentation and end repair, poly-A tail attachment, adapter ligation, size selection, amplification, and purification, sequencing (2 x 150 bp) was performed via NovaSeq 6000 (Illumina).

The raw sequence files in fastq format returned from Novogene were run through FastQC v0.11.9 [34] both before and after trimming to check the overall quality of the reads. The trimming was performed by fastp v.0.20 [35]. Only reads which were both longer than 50 bp and were of mean quality of 25 were processed further.

Alignment and mapping

The reads which passed the quality control were mapped on the reference genome of Perca fluviatilis [23] using hisat2 v.2.1.1 [36] using default parameters. The produced .sam files were subsequently processed with samtools v.1.10 [37]. Lastly, the mapped reads were extracted in bam format for subsequent differential expression analysis.

Differential expression

Analysis for differentially expressed genes (DEGs) was performed in R v.4.2.2 [38] using the DESeq2 v.1.36.0 [39] package. When designing the DESeq dataset object, we considered infection status and population as fixed factors, and the DESeq model internally corrects for potential differences in library sizes. Genes with an adjusted p-value (p-adj) ≤ 0.05 [40] were considered as significantly differentially expressed between infected and uninfected individuals. Human orthologue genes were obtained via Ozerov et al. [22], and DEGs without human orthologues were manually searched using BLAST.

Gene ontology (GO) analysis

GO enrichment was performed using GOrilla [41] separately for both liver and spleen samples. DEGs were compared with all expressed genes from each respective tissue.

Sequencing resulted in an average of 45.1 and 47.8 million raw reads for every spleen and liver sample, respectively. After trimming and filtering, a total of 432 million clean reads were retained for spleen samples, with the average number of 39.3 million reads per sample (Supplementary file 1). A total of 465 million clean reads were retained for liver samples, with the average number of reads of 42.4 million per sample (Supplementary file 2).

RNAseq analysis for spleen samples revealed 17, 246 genes being expressed (> 1 counts per million), with only 22 genes being differentially expressed between infected and uninfected fish (p-adj ≤ 0.05; Table 2). A heatmap generated from DEGs revealed that samples were segregating based on infection status, except for a single infected sample which was clustered among uninfected fish (Fig. 1A). All except one DEG showed upregulation in infected fish (2x2 contingency table, Fisher's exact test P = 0.0015). Identified DEGs were primarily encoding for membrane-bound proteins such as adhesion molecules and receptors (GPIA, SYTL3, BTN2A1), kinase binding (MIDN, AP1B1, DUSP4), cell death and tumorigenesis (SIK1, THBS1) as well as were uncharacterized or unknown genes (LOC120571416, LOC120570956, LOC120573523, LOC120557941, si:ch73-335l21.4, LOC120555327) (Table 2). Tumour suppression and related oncogenes (JUN, JUND, RDH12) were also observed. The majority of genes found to be up- or down-regulated in the spleen relate to host immune response, metabolism, stress response, and membrane-associated proteins (Table 2). However, formal Gene Ontology (GO) analysis showed lack of functional enrichment among DEGs.

Table 2

Summary statistics and gene information for 22 DEGs (*p-adj ≤* 0.05) in spleen between infected and uninfected *P. fluviatilis* individuals.
Genbank ID	Base mean (Infected)	Base mean (Uninfected)	log2 Fold Change	p-value	p-adj	Gene name	Gene ID
PFLUV_G00160980	222.75	99.89	1.97	1.32E-11	1.23E-07	uncharacterized LOC120571416	N/A
PFLUV_G00160960	163.54	17.56	3.38	1.43E-11	1.23E-07	uncharacterized LOC120570956	N/A
PFLUV_G00137210	242.75	54.2	2	1.60E-10	9.15E-07	midnolin-like	MIDN
PFLUV_G00146270	1608.68	460.33	1.61	3.43E-10	1.48E-06	salt-inducible kinase 1	SIK1
PFLUV_G00160970	89.23	6.63	4.17	1.66E-09	5.69E-06	uncharacterized protein LOC120571417 isoform X1	N/A
PFLUV_G00169820	178.7	23.66	3.01	6.68E-09	1.91E-05	uncharacterized protein LOC120573523	N/A
PFLUV_G00042630	250.63	79.28	1.9	3.10E-08	7.60E-05	probable nuclear hormone receptor HR38	N/A
PFLUV_G00114330	2619.87	884.36	1.68	4.11E-08	8.82E-05	transcription factor AP-1	JUN
PFLUV_G00234600	3792.66	1154.08	1.75	3.92E-07	0.000748084	thrombospondin-1-like	THBS1
PFLUV_G00093590	1039.83	845	0.41	5.16E-07	0.000885785	glucose-6-phosphate isomerase a	GPIA
PFLUV_G00165910	197.7	59.92	1.77	7.91E-07	0.001235261	E3 ubiquitin-protein ligase-like	N/A
PFLUV_G00223220	208.77	86.83	1.05	3.05E-06	0.004362188	arginine vasopressin-induced protein 1-like	AVPO1
PFLUV_G00214770	289.01	151.81	1.01	4.10E-06	0.005413646	synaptotagmin-like protein 3	SYTL3
PFLUV_G00257880	609.91	415.74	0.48	9.00E-06	0.01017912	retinol dehydrogenase 12: like	RDH12L
PFLUV_G00277620	458.37	200.03	1.88	9.19E-06	0.01017912	uncharacterized protein LOC120555327	N/A
PFLUV_G00132110	484.34	248.1	0.88	9.48E-06	0.01017912	transcription factor AP-1-like	AP-1
PFLUV_G00054610	435.84	132.77	1.71	1.53E-05	0.015501048	nuclear receptor subfamily 4, group A, member 1	NR4A1
PFLUV_G00004570	2519.13	1093.24	1.03	2.37E-05	0.022595861	Unknown	N/A
PFLUV_G00139600	1160.74	524.36	1.17	3.04E-05	0.027506318	transcription factor jun-D-like	JUND
PFLUV_G00051240	10006.48	19495.98	-0.95	3.82E-05	0.032055553	butyrophilin subfamily 2 member A1-like	BTN2A1
PFLUV_G00199970	1436.69	747.55	0.87	3.95E-05	0.032055553	LOW QUALITY PROTEIN: dual specificity protein phosphatase 4	DUSP4
PFLUV_G00008200	176.2	76.43	1.08	4.10E-05	0.032055553	low density lipoprotein receptor b	LDLRB

RNAseq analysis for liver samples revealed 15, 377 expressed genes (> 1 counts per million), with only ten genes being differentially expressed (DE) between infected and uninfected fish (p-adj ≤ 0.05; Table 3). Like the spleen, a heatmap generated from DE genes in liver revealed incomplete segregation of samples based on infection status (Fig. 1B). Lymphocyte and cell differentiation (ACSF2), galactose-specific lectin nattectin, as well as binding proteins and cell adhesion molecules and their catalysts (LMNA, FABP1, CADM4, CDAB, APBB1IP, FTCD) were among DEGs. Two DEGs (BTN3A2, NRG3B) were related to transcription factors involved in the host adaptive immune response. In contrast to spleen, up- and downregulation of DEGs in liver occurred evenly (2x2 contingency table, Fisher's exact test P = 1). Similar to the spleen, GO analysis showed lack of functional enrichment among DEGs.

Table 3

Summary statistics and gene information for ten DEGs (*p-adj ≤* 0.05) in liver between infected and uninfected *P. fluviatilis* individuals.
Genbank ID	Base mean (Infected)	Base mean (uninfected)	log2 Fold Change	p-value	p-adj	Gene name	Gene ID
PFLUV_G00169300	111.07	636.76	-2.46	1.32E-10	1.99E-06	lamin-A-like	LMNA
PFLUV_G00169310	20.67	393.12	-3.04	2.75E-07	0.00207	butyrophilin subfamily 3 member A2-like isoform X2	BT3A2
PFLUV_G00177580	37.58	2.26	6.02	4.19E-06	0.018592	medium-chain acyl-CoA ligase ACSF2: mitochondrial-like isoform X1	ACSF2
PFLUV_G00150020	99.55	9776.31	-6.83	4.93E-06	0.018592	galactose-specific lectin nattectin-like isoform X1	N/A
PFLUV_G00072130	982.28	273.76	2.22	6.51E-06	0.019055	fatty acid-binding protein, liver-type-like	FABP1
PFLUV_G00087640	63.21	258.32	-1.67	7.58E-06	0.019055	cell adhesion molecule 4	CADM4
PFLUV_G00243290	95.47	15	2.88	9.77E-06	0.021038	neuregulin 3b	NRG3B
PFLUV_G00041980	116.83	390.21	-1.68	1.34E-05	0.025163	cytidine deaminase b	CDAB
PFLUV_G00257980	870.56	350.03	1.3	1.69E-05	0.028373	amyloid beta (A4) precursor protein-binding, family B, member 1 interacting protein	APBB1IP
PFLUV_G00277100	5813.36	11217.62	-0.83	1.89E-05	0.028451	formimidoyltransferasecyclodeaminase	FTCD

Parasitic infections can have severe effects on host physiology, immune system function, survival, and performance [42]. Many freshwater populations of fish are at risk to a wide range of parasites [2, 13, 32, 43] which can have broad implications on the health and well-being of the host. However, not all infections have a severe or detrimental effect on the host and its fitness. In this study, we found that T. nodulosus plerocercoid infection evoked a rather subtle host response on both spleen and liver transcriptomes of P. fluviatilis. This suggests that moderate T. nodulosus plerocercoid load likely has only a weak effect on host metabolism and condition.

Given that the liver is a major metabolic hub and the target tissue for T. nodulosus plerocercoids enduring physical abrasion during encysting, we anticipated that a pronounced transcriptome-wide response to liver infection would predominantly reflect the effect of parasite on host condition, feeding and response to physical damage. Instead, T. nodulosus infection was associated only with a subtle transcriptomic response in perch, which most likely reflects a weak effect of the parasite infection on host metabolism and physiological condition. Yet, several DEGs in perch (e.g., FABP1, BT3A2, LMNA, CADM4, APBB1IP) have been shown to associate with various parasite infections and liver ailments in other host-parasite systems; for example, Rojas et al. [44] found an increase in immune- and fibrosis-related genes as a result of trematode Fasciola hepatica infection in sheep liver. Similarly, one of the upregulated genes in perch liver, LMNA (LOC120572191), provides increased structural integrity for the cell as component of the fibrous nuclear lamina, and has been shown to be involved with liver fibrosis [45]. We also found down-regulation of inhibitors associated with wound healing and cell death (APBB1IP, CADM4) and upregulation of neutrophil chemotaxis genes and transcription factors (CDAB, Galactose-specific lectin nattectin) associated with host immune response.

Due to the spleen’s key role in immune defence, we anticipated that a high proportion of DEGs in the spleen would reflect strong immune response of the host against the parasite. Yet, we found a small number of DEGs in the spleen (n = 22) among which there were several genes without known human orthologs (n = 8). The lack of strong transcriptome-wide response may stem from a couple of processes. One such possibility is that T. nodulosus infection has an overall low physiological effect which does not provoke a strong host immune response and fish are able to cope with low to moderate levels of parasite burden. In contrast, parasite infections often cause major changes in specific host tissues involving hundreds or thousands of genes reflecting a major systemic response; for example, over 200 DEGs and a strong immune functioning GO process enrichment was observed in perch eye tissues in association with Diplostomidae infections [46]. It is also possible that T. nodulosus is able to evade triggering the host immune system, such as the spleen or even other immune-privileged sites [47]. For example, trematodes which can coat their surfaces in a complex which degrades host antibodies and thus allows the parasite to avoid the host’s immune response [47, 48]. Fasciola hepatica has also been shown to evade host immunity, despite drugs and other procedures such as vaccination and chemotherapy [49].

Despite of low number of DEGs, they indicate some degree of impact on the host. For example, one of the uncovered DEGs (JUN) is an oncogenic transcription factor which has been associated with anti-apoptotic properties, immune response, and cell death [50, 51]. Genes belonging to this family of transcription factors have been upregulated in mice, when infected by a helminth parasite (Taenia crassiceps or Taenia solium) [52]. This present study has found both an increased expression of AP-1, NR4A1, and THBS1 orthologs in infected perch. Infection in bovines by the tick-borne Thallia annulata and Thallia parva parasites has also been shown to result in an increased expression of the AP-1 transcription factor and an associated upregulation of JUN protein. Recently it has been reported that mice infected with the liver parasite Entamoeba histolytica showed an upregulation of NR4A1, a transcription factor responsible for regulation macrophages in the host [53]. Additionally, it has been discovered that when three-spined stickleback (Gasterosteus aculeatus) are infected by the helminth parasites Diplostomum pseudospathaceum and Schistocephalus solidus, one of the few genes that was upregulated because of the infection was the THBS1 gene [54], which is associated with both cellular matrix and cell-cell interactions [55]. Finally, upregulation of SIK1 in infected perch coincides with an analysis by Kang et al. [56], who found a significant correlation between SIK1 and a negative prognosis in patients suffering from diffuse large B-cell lymphoma. While speculative, this may be relevant for other parasites, including various because liver and blood flukes (Opisthorchis viverrini, Opisthorchis felineus, and Clonorchis sinensis) that have been categorized as Group 1 carcinogens by the World Health Organization [57]. Taken together, these studies demonstrate that while subtle, these genes shown to be differentially expressed in P. fluviatilis spleens seem to be involved in host-pathogen responses in diverse systems, and despite the mild response observed in the present study, the effect of these genes can be significant to the host.

Prior research has shown that perch can survive and withstand infection by T. nodulosus plerocercoids for years in its natural environment [4]. Our findings support this by identification of only a small total number of DEGs across two tissues and corroborates earlier work by Masson et al. [30] which demonstrated a relatively weak physiological effect (hepatosomatic index, body condition index, and others) of T. nodulosus plerocercoid infection on P. fluviatilis. However, our results are to some extent at odds with Brinker & Hamers [31], who found a stronger physiological effect (on growth) which was linked to the severity of T. nodulosus infection. A potential reason for this difference may be related to the varying infection tolerance across perch ontogeny coupled with the selective disappearance of the weakest individuals. Here, we sampled mature Eurasian perch individuals (2 + years) that have already survived their most vulnerable and challenging stages of development. Thus, it is entirely possible we would see a more pronounced effect of T. nodulosus infection in juveniles that initially suffer plerocercoid formation and are expected to have competing resource demands between immune function (current survival) and growth (future survival). Considering the described effects during reproduction [4], it is also possible that a stronger response to infection would be observed during the breeding season, which is especially demanding for egg producing females [58].

Evidence across different host-parasite systems indicates that infection often increases the likelihood of predation [59, 60], but this phenomenon is far from universal [30]. To maximize the likelihood for reaching its final host (Northern pike), the pike flatworm may benefit from weakening perch to predation and thus completing its life cycle, but this has yet to be shown conclusively [32]. However, if the Eurasian perch is unable to carry such a parasitic burden and dies before being eaten by the pike, it does not represent an optimal reproductive strategy for T. nodulosus. Rather, it is in the parasite’s interest that the intermediate host can cope with the infection and live until being predated by pike. Therefore, it makes sense prima facie that the more optimal strategy for the parasitic flatworm would be to induce only mild response in the intermediate host and our transcriptomic analysis corroborates this.

While the definition of ‘parasite’ commonly implies that one organism benefits at the expense of another organism [61], the actual cost of the parasitism may vary from lethal to essentially negligible. Hosts may harbour dozens to many hundreds of parasites, including many different parasite species. Therefore, it has been suggested that it is more fitting to describe the impact of being parasitized as range of effects which exist on a spectrum, whose ranges can extend from mild or virtually asymptomatic, to severe or even lethal [25, 62–65]. However, it is likely that there exists a bias among current transcriptomic studies focusing on highly virulent or harmful parasites because understanding of most dangerous pathogens is often prioritized in medical, veterinary, or ecological research. Yet, given the incredible diversity of parasitic life-forms, it is likely that many parasites have only a small effect on host fitness at least during a certain period. Our study therefore represents one of such examples where a parasite, despite its conspicuous nature, evokes only a subtle physiological response from the host.

This study provides first transcriptomic insights into the Eurasian perch response to pike tapeworm plerocercoid infection. Our results show that P. fluviatilis displays a subtle response at the level of gene expression both in liver and spleen tissues. This suggests that moderate T. nodulosus plerocercoid load has only a weak effect on host metabolism and condition and does not invoke a strong immune response. Therefore, our findings demonstrate that not all conspicuous infections have severe effects on host gene regulation.

DEG: Differentially expressed gene

PCR: Polymerase chain reaction

RNAseq: RNA Sequencing

TL: Total length

GO: Gene ontology

Acknowledgements

We would like to thank the CSC-IT Center for Science at the Finnish Functional Genomics Centre for access to their high-performance computing resource, Puhti. We would also like to thank Magnus Lauringson and Alfonso Diaz-Suarez for their help in the field.

Funding

Support for the study was provided by Estonian Research Council grant (PRG852 to RG), Swedish Research Council grant 2020-03916 (to AV), and the Kristjan Jaak Foundation scholarship (to KT).

Availability of data and materials

Sequence data will be made available upon publication. Environmental and morphological data are included in this published article and supplementary information files.

Authors’ contributions

KT was responsible for laboratory work, data analysis, manuscript writing, figure and table construction, and data interpretation. KN contributed to the original study design, sample collection, manuscript writing, and data interpretation. AV contributed to the original study design, sample collection, manuscript writing, and data interpretation. SK contributed to sample collection. MO contributed to data analysis and data interpretation. All authors read and approved the final manuscript.

Ethics approval and consent to participate

None.

Consent for publication

All authors give consent for publication.

Competing interests

The authors declare no competing interests.

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Subtle transcriptomic response of Eurasian perch (Perca fluvatilis) associated with Triaenophorus nodulosus plerocercoid infection

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Background

Methods

Fish collection and tissue preparation

RNA extraction

Library preparation, sequencing, and quality assessment

Alignment and mapping

Differential expression

Gene ontology (GO) analysis

Results

Discussion

Conclusions

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