Running title: Inducible responses to multiple predators
Lei Gu, Shanshan Qin, Yunfei Sun, Jing Huang, Siddiq Akbar, Lu Zhang,
Zhou Yang*
Jiangsu Province Key Laboratory for Biodiversity and Biotechnology,
School of Biological Sciences, Nanjing Normal University, 1 Wenyuan
Road, Nanjing 210023, China
* Corresponding author: Zhou Yang
TEL: +86-25-85891671.
E-mail: yangzhou@njnu.edu.cn
Jiangsu Province Key Laboratory for Biodiversity and Biotechnology,
School of Biological Sciences, Nanjing Normal University, 1 Wenyuan
Road, Nanjing 210023, China
Abstract
Inducible defenses of prey are evolved under diverse and variable
predation risks. In the co-evolution of prey and multiple predators with
antagonistic selection pressures, whether inducible defense responses of
prey will fall into a dilemma and its underlying mechanism are still
unclear. Based on the antagonistic predation pressure from invertebrate
predator Chaoborus larvae and vertebrate predator fish, we
studied multi-traits and transcriptome of the freshwater crustaceanCeriodaphnia cornuta under multiple predation risks. Our results
showed that Chaoborus larvae predation risks altered the
expression of genes encoding cuticle protein and changed the
biosynthesis of steroid hormone, cutin, suberine, and wax, promotingCeriodaphnia to express horns and grow larger at a late
development stage, whereas fish predation risks mainly triggered
responses in genes encoding ribosome and pathways of unsaturated fatty
acids biosynthesis, cysteine and methionine metabolism, resulting in a
smaller individual size and earlier reproduction. The inducible
responses on transcription and individual traits both revealed that
predator unique responses are dominant and the antagonistic responses
are the least. Besides, Pearson correlations between different predator
unique responses are extremely weak. Furthermore, the unique individual
traits triggered by different predators can be expressed simultaneously.
These results indicated that Ceriodaphnia can avoid the dilemma
by performing predator unique responses and diverse inducible responses
are favored in the co-evolution of zooplankton and multiple predators.
Keywords: Cladoceran; Chaoborus ; Fish; Inducible
defense; Predation risk
Introduction
In the co-evolution of predator and prey, defense is critical to the
survival of prey. Because of the changing predation risks, inducible
defenses, triggered by predation cues, are favored by prey (Tollrian &
Harvell, 1999). To successfully defend predators, prey organisms can
perform various inducible defensive traits, including behavior (De
Meester, 1993), morphology (Gu et al., 2021), chemical substance
(Selander et al., 2015), and life history (Kvile, Altin, Thommesen, &
Titelman, 2021). Since diverse predation risks can prevent the stable
expression of an inducible defensive trait (Steiner & Auld, 2012), the
present study seeks to understand how a prey response to multiple
predation risks, especially to predators with antagonistic selection
pressures.
Inducible defenses are common in aquatic organisms, such as
phytoplankton (Lürling, 2020), zooplankton (Diel, Kiene,
Martin-Creuzburg, & Laforsch, 2020), amphibians (Mitchell,
Bairos-Novak, & Ferrari, 2017), and fish (Brönmark & Miner, 1992).
Through integration of inducible defense researches, the present study
classified the responses against multiple predators into two major
categories. The first type is the general response, which evolves
through diffusion co-evolution and is a reciprocal adaptation to similar
predators, for example, mayfly preforms the same avoidance behavior
under different fish predation risks (Alvarez, Landeira-Dabarca, &
Peckarsky, 2014); the other type is the specific response, which is
evolved by pairwise co-evolution between specific predator and prey,
such as the immune responses of immune systems to pathogens (Westra et
al., 2015) and the inducible crests of Daphnia in response toNotonecta predation (Grant & Bayly, 1981). By considering the
specific responses in different traits, they can be further subdivided
into antagonistic responses on the same trait and unique responses on
separate traits. Assuming the selection pressures are antagonistic, if
the prey mainly performs antagonistic responses on the same traits, then
inducible responses to one predator may cause the prey suffer an
environmental cost, i.e., vulnerable to the other predator; if the
unique responses on separate traits dominate, then the complex defense
responses may create maintenance costs, i.e., energetic costs of the
sensory and regulatory mechanisms (Auld, Agrawal, & Relyea, 2010).
Based on this, we cannot theoretically speculate whether inducible
responses of prey against antagonistic predation risks are limited and
in a dilemma.
In aquatic ecosystems, cladocerans are in the middle of the food chain,
providing food resources for insects and fishes (Miner, De Meester,
Pfrender, Lampert, & Hairston, 2012). These invertebrate and vertebrate
predators constitute antagonistic selection pressures on the size or
habitat selection of waterfleas, for example, larger plankton is
vulnerable to the large visual predator fish, while less vulnerable to
the small ambush predator Chaoborus larvae (Swift, 1992).
Thereby, antagonistic inducible traits are commonly expressed byDaphnia , for example, Daphnia hyalina shows completely
opposite response in size and reproduction under fish and invertebrates
predation pressure (Stibor & Lüning, 1994); Daphnia galeataprefers deeper habitat under fish predation risk, while inhabits the
upper layer under Chaoborus larvae predation risk (Dodson, 1988).
Besides, unique inducible defensive traits are prominent inDaphnia , such as “twist” (Herzog, Rabus, Ribeiro, & Laforsch,
2016), neck teeth (Tollrian, 1993), and horns (Gu, Qin, Zhu, et al.,
2020). Furthermore, general responses are noticeable, such as the
elongated tail spine, which is observed in Daphnia in response to
fish, Triops , and Notonecta (Gu, Qin, Lu, et al., 2020;
Ritschar, Rabus, & Laforsch, 2020). Consistent with the summary of
inducible defensive traits, both general and specific responses appear
at molecular levels, for instance, Daphnia magna decreases actin
and tubulin expression under the predation risk of Chaoboruslarvae or fish (Pijanowska & Kloc, 2004), increases the expression of
ribosomal protein and vitellogenin under fish predation risks (Effertz,
Mueller, & von Elert, 2015), while decreases the expression of
vitellogenin and increases cuticle protein under Triops predation
risks (Otte, Fröhlich, Arnold, & Laforsch, 2014). Therefore, in the
summary of Daphnia researches, this typical research organism
shows various types of responses under antagonistic predation risks.
However, through these scattered studies on different Daphniaspecies and clones, we still cannot conclude which type of response is
preferred by a prey.
Ceriodaphnia cornuta is a widely distributed species with
sensitive inducible defensive traits (Gu et al., 2021; Qin et al.,
2021), providing a suitable organism for answering the above question.
Since some inducible traits are hidden (Laforsch, Ngwa, Grill, &
Tollrian, 2004), researches on a few traits are not sufficient. In
recent years, omics technologies promote our understanding of the
mechanisms of inducible defenses (Hales et al., 2017; Zhang et al.,
2021). Therefore, to systematically answer how a prey response to
antagonistic predation risks, the present study tested multi-traits and
transcriptome of C. cornuta in response to Chaoboruslarvae and fish. Besides, to better understand the strategy of inducible
responses, we analyzed the Pearson correlation between different
inducible responses.
Materials and methods
Predation risks
The predation risks were simulated by different predator-conditioned
medium, which was prepared according to Gu, Qin, Zhu, et al. (2020). We
cultured 4 Rhodeus ocellatus or 100 Chaoborus sp. larvae
in aged tap water and fed enough C. cornuta for 6 h, and then
transferred them into 2 L of COMBO medium (Kilham, Kreeger, Lynn,
Goulden, & Herrera, 1998) for 18 h. The stock predator-conditioned
medium, containing different predator kairomones (Hahn, Effertz, Bigler,
& von Elert, 2019; Weiss et al., 2018), were filtered through a 0.22 μm
glass fiber filter (Millipore) and then the filtrates were stored in a
refrigerator before the experiments. To test the response ofCeriodaphnia against fish, as well as Chaoborus , we set up
a full factor experiment containing the following treatments: The
control (C) treatment was COMBO medium; Fish (F) and Chaoborus(CH) predation risk treatments were produced by diluting their filtered
stock medium 20 times (i.e., 1 fish per 10 L) and 2.5 times (i.e., 20Chaoborus larvae per L) in COMBO medium, respectively; the
combination treatment (CH + F) consisted of the above two diluted
medium.
Life history experiment
The C. cornuta clone used in the present study was sampled from
Lake Taihu (31°22′13.548″N, 120°0′16″E), China. We cultured C.
cornuta in COMBO medium and fed with Chlorella pyrenoidosa (1.5
mg C/L) at 25 °C under a fluorescent light intensity 500 Lux in a 14:10
h light/dark cycle. Synchronous C. cornuta with a density of 1
ind per 10 mL were adapted to the above conditions for at least two
generations. We randomly divided newborn individuals into different
treatments within 12 h. Each individual was cultured in 10 mL medium
with 10 replicates for each treatment and the media in different
treatments were refreshed daily.
The body size and horns were detected at maturity and a late
developmental stage, i.e., the 16th day. We scored the horns of C.
cornuta according to Gu et al. (2021), i.e., absent (score 0), small
(score 5), and large (score 10), and then the individual scores were
normalized by a maximum point to define the induction levels between 0%
and 100%. Besides, time to the first brood, neonate size, brood number,
total offspring number, and average brood size were recorded in the
present study.
RNA samples and
sequencing
To further analyze the type of responses on the transcriptional level,
we sequenced the transcriptome of C. cornuta under C, F, and CH
treatments. Groups of 250 newborn individuals were cultured in 2.5 L
medium with 3 replicates for each treatment. During this cultivation,
responses triggered by different predation risks were verified through
inducible traits, i.e., horns and body size at maturity. We refreshed
the medium daily and took samples within 12 h after the first brood ofC. cornuta . Ceriodaphnia samples were frozen in liquid
nitrogen and homogenized in TransZol Up, and the total RNA was extracted
using TransZol Up Plus RNA Kit following the manufacturer’s instructions
(ER501, TRANS, China). RNA quality was assessed by an Agilent 2100
Bioanalyzer (Agilent Technologies, USA) and checked by agarose gel
electrophoresis. In the present study, the RNA integrity number of all
samples was above 7.0.
The total mRNA of Ceriodaphnia was enriched by Oligo (dT) beads,
then the enriched mRNA was fragmented into short fragments using
fragmentation buffer and reverse transcribed into cDNA with random
primers. The cDNA fragments were purified, end repaired, poly(A) added,
and ligated to Illumina sequencing adapters, then the ligation products
were size selected and PCR amplified to develop a cDNA library. Finally,
the cDNA library was sequenced using Illumina HiSeqTM4000 by Gene Denovo Biotechnology Co. (Guangzhou, China).
Transcript assembly and
annotation
Since the genomic sequencing in Ceriodaphnia has not been
conducted to date, we adopted De Novo RNA-Seq to analyze the
transcriptome of C. cornuta . To get high-quality clean reads,
sequenced reads were cleaned up by removing reads containing adapters,
more than 10% of unknown nucleotides (N), and low-quality reads
(Q-value≤20). Clean reads were assembled into unigenes using the Trinity
program (Grabherr et al., 2011). To annotate the unigenes, we used the
BLASTx program with an E-value (<10-5) to
NCBI non-redundant protein (Nr) database, the Swiss-Prot protein
database, the Kyoto Encyclopedia of Genes and Genomes (KEGG) database,
and the COG/KOG database. Protein functional annotations could then be
obtained according to the best alignment results.
Quantification of gene expression and RT-qPCR
Analysis
The unigene expression was calculated and normalized to RPKM (Reads Per
kb per Million reads) (Mortazavi, Williams, McCue, Schaeffer, & Wold,
2008). RNAs differential expression analysis was performed by DESeq2
software between control and different predation risk treatments. The
genes with the parameter of false discovery rate (FDR) below 0.05 and
absolute fold change ≥ 1 were considered differentially expressed genes
(DEGs). We classified the DEGs into different types according to our
classification and then used KEGG analysis to classify the function of
DEGs. Pathways with P -value ≤ 0.05 were considered as
significantly enriched pathways. The representative DEGs of different
significantly enriched pathways were selected according to the following
precedence conditions: stable expression, large fold change, and the
pathways are annotated on a closely related species, i.e., D.
magna and D. pulex .
To validate the RNA-Seq data in C. cornuta transcriptome, we
quantitated the expressions of 18 random DEGs by RT-qPCR. ddH2O was used
as the negative control in RT-qPCR. The cDNA was synthesized from mRNA
by Reverse Transcriptase SuperMix (R233, Vazyme, China), and RT-qPCR was
conducted using ChamQ Universal SYBR qPCR Master Mix (Q711, Vazyme,
China). All the primer sequences are presented in Supplementary Table 1.
We obtained expression data from four alternative reference genes
(Scoville & Pfrender, 2010) and calculated their average gene
expression stability by geNorm. The glyceraldehyde-3-phosphate
dehydrogenase (G3PD), the RNA polymerase II gene (RNAP II), and the
elongation factor 1-alpha gene (EF) were determined to be stably
expressed and were geometrically averaged to calculate a gene expression
normalization factor for each sample. Gene expression was calculated
using 2-ΔΔt method. Correlation between RNA-Seq and
RT-qPCR was performed by regression analysis.
Statistical Analysis
To test the effects of different predation risks, a MANOVA, followed by
two-way ANOVA, was performed on individual traits. The significant
differences (P < 0.05) among different treatments were
tested by the Bonferroni test. When the normality test (Shapiro-Wilk)
failed, we used Scheirer-Ray-Hare followed by Wilcoxon rank-sum test to
analyze the differences between treatments. To test the relationship
between different types of response, we analyzed the Pearson correlation
coefficient between traits, as well as representative DEGs, in different
categories. The statistical tests were performed using R software
(version 3.6.2).
Results
Morphology and life history
traits
Different predation risks significantly triggered various responses in
morphology and life history traits (Table 1). Compared with control, the
responses induced by fish and Chaoborus larvae predation risks
could be classified into the following four categories (Fig. 1): (1)
Unique responses to Chaoborus larvae: horn expression (at
maturity and 16th day) and total offspring number, i.e., C.
cornuta expressed horns (maturity: P < 0.001; 16th
day: P < 0.001) and increased offspring number
(P = 0.002) under Chaoborus larvae predation risk, and the
traits were not significantly changed by fish predation risk. (2) Unique
responses to fish: time to first brood and neonate size, i.e., the
neonate size (P = 0.006) and time to first brood (P< 0.001) of C. cornuta were remarkably decreased under
fish predation risk, and these responses were not significant underChaoborus larvae predation risk. (3) General responses: Size at
maturity and brood number, i.e., the size (CH vs. C: P = 0.007; F
vs. C: P < 0.001) and brood number (CH vs. C: P= 0.006; F vs. C: P = 0.017) were significantly decreased under
fish and Chaoborus larvae predation risks. (4) Antagonistic
responses: size at 16th day, i.e., C. cornuta increased the size
under Chaoborus larvae (P = 0.034), but decreased the size
under fish predation risks (P < 0.001). Additionally,
no significant differences were observed in average brood size. Among
all those traits, unique responses to predators were dominant, i.e.,
unique responses (5) > general responses (2) >
antagonistic responses (1).
Interactions between fish and Chaoborus larvae predation risks
were noticeable in different traits (Table 1). General responses: size
at maturity in the combination treatment was smaller than that in
control (P <0.001) and had no significant difference
with that in fish predation risk treatments; brood number of the
combination treatment did not have remarkable differences with that of
other treatments. Unique responses: time to first brood (CH + F vs. C:P = 0.027) and neonate size (CH + F vs. C: P = 0.003) were
significantly decreased in the combination treatment and had no
significant differences with those in fish predation risk treatment;
horn expression in the combination treatment was significant at maturity
(CH + F vs. C: P = 0.007), while this inducible trait was greatly
impaired when compared with that of Chaoborus larvae predation
risk treatment (maturity: P = 0.012; 16th day: P
< 0.001). Antagonistic responses: size at 16th day in the
combination treatment was significantly smaller than that inChaoborus larvae predation risk treatment (P <
0.001), higher than that in fish predation risk treatment (P =
0.065), and not different from that in control (P = 0.764).
Overview of assembled
transcriptome
We obtained 78341484, 72493072, and 69930191 clean reads in C, CH, and
F, respectively. A total of 37120 assembled unigenes were assembled
through Trinity software and each sample contained more than 66.54%
assembled unigenes (Supplementary Table 2). By comparing with Nr, KEGG,
COG, and SwissProt databases, a total of 18343 unigenes (49.4%) were
annotated in these public databases (Supplementary Fig. 1). Regarding
the species distribution in the Nr database, C. cornuta had the
highest comparison rate with Daphnia magna (26.33%), followed byD. pulex (2.6%) (Supplementary Fig. 2A); the unigenes enriched
in the KOG database were classified into transcription, ribosomal
structure, and gene replication, recombination, and repair
(Supplementary Fig. 2B); the annotated GO terms were mainly associated
with metabolic process, cellular process, cell part, and binding
(Supplementary Fig. 2C).
Differentially expressed genes
(DEGs)
Paired samples within the same treatment had high Pearson correlation
coefficients (≥0.90) and were clustered together in principal component
analysis (Fig. 2A and B), which conformed to requirements of biological
repetition. Furthermore, the expression patterns showed a significant
correlation between RT-qPCR and RNA-Seq (Fig. 2C (a)R 2 = 0.936; (b) R 2 =
0.788), indicating that our analysis on the expression data by RNA-Seq
is reliable.
Compared with control, Chaoborus larvae and fish predation risk
significantly affected the expression of 1515 and 846 genes,
respectively (Fig. 3A). Among them, there were 1399 unique DEGs in CH,
730 unique DEGs in F, 114 general DEGs, and 2 antagonistic DEGs (Fig.
3B). Therefore, unique responses to predators were dominant at the
transcriptional level, i.e., unique DEGs (2129) > general
DEGs (114) > antagonistic DEGs (2) (Supplementary Table 3).
Considering the DEGs caused by different predators, we further analyzed
the differences in the enriched pathways of C. cornuta(Supplementary Table 4) and concluded the main DEGs and pathways related
to inducible defensive traits (Table 2). The DEGs of C. cornutaagainst Chaoborus larvae, including cuticle protein, fatty
acyl-CoA reductase, and trypsin genes, were mainly enriched in cutin,
suberine and wax biosynthesis, protein digestion and absorption, and
steroid hormone biosynthesis; the DEGs of C. cornuta against
fish, containing ribosomal protein, actin, and short-chain type
dehydrogenase genes, were mainly enriched in cysteine and methionine
metabolism, ribosome, phototransduction, and biosynthesis of unsaturated
fatty acids; the general DEGS, including cysteine proteinase, HSP70,
actin, and alpha-tubulin genes, were enriched in the pathways of
apoptosis and antigen processing and presentation.
Correlation analysis between different inducible
responses
Both 9 individual traits and 40 representative DEGs (Supplementary Table
5) revealed high Pearson correlations within unique responses to fish orChaoborus larvae (Fig. 4), such as the response of horns at
maturity was significantly correlated with the changes of horns at 16th
day (P = 0.05) and total offspring number (P = 0.05).
Besides, both correlation analyses showed weak Pearson correlation
coefficients between unique responses to fish and unique responses toChaoborus larvae. While, a few significant correlations appeared
on the weak correlation area in the transcriptional expression, such as
Unigene0008297, in ribonucleoprotein component protein expression, had
significant positive relationships with Unigene0027903 (P= 0.049)
and Unigene0005204 (P= 0.013) in Aspartokinase and
Adenosylhomocysteinase expression, respectively (Fig. 4; Supplementary
Table 5).
Discussion
Our experiments clearly showed that C. cornuta performed diverse
responses under the antagonistic predation risks consisted of fish andChaoborus larvae. Based on the classification of inducible
responses, our results revealed, for the first time, that predator
unique responses are dominant, followed by the general responses, and
the antagonistic responses are the least. When the antagonistic
predation risks coexist, unique individual traits triggered by different
predators can be expressed simultaneously, thereby the Pearson
correlations between the unique responses to different predators are
very weak. According to these results, this study supports the view that
prey prefers predator unique responses in the co-evolution of prey and
multiple predators, which may cause complex costs and limitations of
inducible defenses.
Horns and larger size are adaptive inducible traits to Chaoboruslarvae predation (Gu et al., 2021; Riessen & Trevett-Smith, 2009). The
larger individual size at a late development stage requires rapid growth
and more food intake (Gianuca, Pantel, & De Meester, 2016), thereby
promoting the brood number and total offspring number. The horns are
formed by the carapace, which is composed of two layers of dermal cells
and covered by chitin, which combines with cuticle protein (Charles,
2010). Therefore, the formation of morphological defensive traits
involves a series of changes in the expression of chitin, hormones, and
epidermal formation genes at different times (Christjani, Fink, &
Elert, 2016; Miyakawa et al., 2010), as well as the regulation of
epidermal cell growth by endocrine hormones (Weiss, Leese, Laforsch, &
Tollrian, 2015). In this study, significant changes in genes and
pathways were involved in cuticle protein, cutin, suberine, and wax
biosynthesis, and steroid hormone biosynthesis. These genes’ expression
may promote the synthesis of related substances (Fig. 5) and regulate
individual growth (Edgar, 2006). However, growth and development of
cladocerans require continuous molting and formation of new carapace,
thus, the maintenance of horns needs continuous substance synthesis,
which may result in continuous distribution costs (Auld et al., 2010).
Besides, Chaoborus predation risks altered the digestion and
absorption of C. cornuta , such as the trypsin gene, which may
affect the digestion and resource allocation strategy (Von Elert et al.,
2004).
The smaller size, earlier reproduction, and increased brood number are
adaptive responses to fish predation risks, which are similar to the
typical responses of other cladocerans under fish predation (Diel et
al., 2020). In terms of gene expressions, our results showed that the
genes encoding the proteins of actin and ribosomal are down-regulated
under fish predation risks. Since actin plays an important role in the
structure of the cytoskeleton, the inhibition of actin may result in a
smaller cladoceran size. Similar results were observed in the studies ofD. magna inducible defenses (Effertz et al., 2015; Pijanowska &
Kloc, 2004). On the contrary, Schwarzenberger, Courts, and von Elert
(2009) revealed an up-regulation of actin genes in D. magna under
fish predation risks. Because gene expression is jointly regulated by
transcriptional regulators and related proteins (Stibor, 2002), the
differential expressions could be observed within 1-2 hours (Effertz &
von Elert, 2014). Ribosomal proteins are responsible for protein
assembly and translation, thus, the down-regulation of ribosomal protein
may inhibit the synthesis of proteins that are needed for individual
growth and development (Zhou, Liao, Liao, Liao, & Lu, 2015), ultimately
affecting the growth of C. cornuta . In the enrichment analysis,
some DEGs can be enriched in multiple pathways. The significantly
enriched phototransduction may change the visual perception ofDaphnia (Mahato et al., 2014), which could be an adaption to
behavioral responses, such as habitat selection (Loose & Dawidowicz,
1994) and escape behavior (Pietrzak, Pijanowska, & Dawidowicz, 2017).
Besides, fish predation can reduce the unsaturated fatty acids of
neonates, causing Daphnia to be vulnerable to starvation (Stibor
& Navarra, 2000), therefore the significantly enriched pathway of
unsaturated fatty acids may alter the distribution of unsaturated fatty
acids. Furthermore, the longevity regulating pathway was significantly
enriched under fish predation risks, which may cause an opportunity
cost, i.e., the decline of lifespan (Dawidowicz, Predki, & Pietrzak,
2010).
When facing different predators, C. cornuta showed general
responses, such as the expression of cysteine protease, heat shock
protein, actin, and tubulin genes. The cDNA sequence of crustacean
cysteine protein is closer to that of insect cathepsin L, which
regulates the molting cycle and programs cell death during development
(Agrawal, Bagchi, & Bagchi, 2005). Thus, the affected cysteine
protease may affect molting and increase brood number in the present
study. The up-regulation of heat shock protein is an adaptive response
various environmental stresses, including predation risks (Pijanowska &
Kloc, 2004). Because this response is rapid and returns to previous
level after long-term treatment (Pauwels, Stoks, & De Meester, 2005;
Pauwels, Stoks, Decaestecker, & De Meester, 2007), the down-regulation
of heat shock protein genes may promote the recovery of heat shock
protein in this study. Similarly, general responses are observed in
actin and tubulin genes of Daphnia (Pijanowska & Kloc, 2004),
they are involved in the formation of the cytoskeleton and other life
activities, while their specific functions still need further researches
(Chen et al., 2018).
From the perspective of different responses, prey performs coupling
responses to the same predator and extremely weak coupling unique
responses to antagonistic predation risks. It is easy to understand that
prey can alter resource allocation strategies under single predation
risk, resulting in an array of adaptive responses (Reede, 1995). For a
successful evolution of predator unique responses under multiple
predation risks, we mainly considered it from the genotype, selection,
and cost. Firstly, the genotypes of cladocerans in ponds or lakes are
highly diverse and the inducible traits of different clones are
uncoupled (Boersma, Spaak, & De Meester, 1998; Decaestecker, De
Meester, & Mergeay, 2009; Stoks, Govaert, Pauwels, Jansen, & De
Meester, 2016). Secondly, in the process of predation, multiple
predators have diversified selection effects, which contribute to
predator unique defensive traits (Herzog & Laforsch, 2013; Heynen,
Bunnefeld, & Borcherding, 2017). Finally, the environmental costs, such
as changing predator regimes, may exceed maintenance costs (
Decaestecker, De Meester, & Ebert, 2002; Tollrian, 1995; Yin, Laforsch,
Lohr, & Wolinska, 2011), thus, complex unique responses are favored by
prey. In our study, this inducible defensive strategy can avoid the
dilemma of responses on single traits, improving the survival rate of
prey under multiple predation risks. For example, smaller C.
cornuta is less likely to be found by fish (O’brien, 1987). At the same
time, horn expression makes C. cornuta less vulnerable toChaoborus larvae predation (Gu et al., 2021). While, the
co-expression of unique inducible defenses is influenced by development,
indicating that there is a trade-off underlying the adaption to multiple
predation risks (Riessen & Gilbert, 2019). Therefore, further studies
are still needed to reveal how prey responses to multiple predators,
especially in a complex biological and abiotic
environment.
Conclusions
Through the responses on individual traits and transcription, this study
revealed inducible responses of C. cornuta againstChaoborus larvae and fish. To cope with such antagonistic
predation risks, C. cornuta mainly changed cuticle gene
expression and formed horns under Chaoborus larvae predation
risk, while altered ribosome genes expression and reduced body size
under fish predation risks. Our analysis on those inducible responses
revealed for the first time that different predator unique responses are
dominant and extremely weak coupling. Contrary to the dilemma of
responses on a few inducible defensive traits, this study supports the
view that zooplankton prefer predator unique responses and performs the
least antagonistic responses in the adaption to antagonistic predation
pressures, implying that the potential co-evolutions with multiple
predators are mutually shaping the inducible responses of zooplankton.