Predation is recognized as an important selective force which has been shown to drive the shape of trophic cascades and numerous aspects of ecosystem ecology (Gliwicz, 1986; Lima, 1998; Werner and Peacor, 2003). Such effects of predators are caused by predation (direct consumptive effect; Preisser et al., 2005) or by effects on plastic behavioral, physiological or morphological traits of prey seeking to avoid predation (indirect, non-consumptive effect, (Heithaus et al., 2008; Lima, 1998; Moll et al., 2017; Werner and Peacor, 2003). The concept has been introduced that prey species must effectively balance consuming their resources against becoming resources for their predators (Abrams, 1984; Sih, 1980) in order to maximize their own fitness. It has become clear that non-consumptive predator effects strongly affect prey distribution, demography and behavior (Heithaus et al., 2008; Lima, 1998; Werner and Peacor, 2003) and the strength of top-down and bottom-up control in communities (Ford et al., 2014). Hence, non-consumptive predator effects are mediated by shifts in plastic traits of prey, and in aquatic food webs such non-consumptive effects exceed direct consumptive effects (Preisser et al., 2005; Turner et al., 2000).

Such adaptive shifts in prey traits require an accurate assessment of the predation risk, which may be accomplished by physical contact, vision or by chemical cues. Chemical cues are superior cues in turbid or dark environments (Kats and Dill, 1998) or in cases in which the escape capability upon attack is low in prey, for example due to low escape velocity. In line with this, the induction of defenses by chemical cues from predators is widespread in aquatic systems (Bjærke et al., 2014; Brönmark and Hansson, 2012), and recently progress has been made by identification of chemical cues involved in aquatic predator-prey chemical communication (Poulin et al., 2018; Selander et al., 2015; Weiss et al., 2018).

One classical example of behavioral predator avoidance is diel vertical migration (DVM) in the freshwater microcrustacean Daphnia, which play a key role in lakes and ponds, as they are major consumers of planktonic primary producers and important prey for higher trophic levels (Miner et al., 2012). DVM is a widespread predator avoidance behavior (Hays, 2003; Williamson et al., 2011), in which the exposure to UV (Rhode et al., 2001) and the risk of predation by visually oriented predators, such as fish, is reduced by daytime residence in the dark, deep layer of the water column (Hays, 2003; Stich and Lampert, 1981). At night, zooplankton emerges from the depth into the upper water layer to minimize demographic costs associated with residence in the cold, food-depleted deep-water refuge (Loose and Dawidowicz, 1994; Stich and Lampert, 1981). Hence, DVM of Daphnia negatively affects the foraging success of planktivorous fish. This behavioral anti-predator defense affects the control of planktonic primary producers by zooplankton in the open water and thus impacts many other ecosystem-wide processes (Haupt et al., 2010; Reichwaldt and Stibor, 2005).

In lakes and ponds, DVM in zooplankton is triggered by changes in light intensity (Effertz and von Elert, 2014; Ringelberg, 1999) and by chemical cues released by predators (Dodson, 1988; Lampert, 1993; Neill, 1990). Such chemical cues are termed kairomones, if they mediate a transfer of information among species that imparts a benefit to the receiving organism while not being beneficial for the producer (Pohnert et al., 2007). The finding that the amplitude of DVM increases with fish density indicates that kairomones provide a reliable indicator for the risk of Daphnia of being preyed upon by fish (Van Gool and Ringelberg, 2002; von Elert and Pohnert, 2000). Thus, fish - Daphnia interactions are to a large degree determined by indirect, non-consumptive effects of fish that are mediated by kairomones inducing predator avoidance by DVM.

Lakes and ponds are the best available freshwater source providing ecosystem services like domestic, industrial and recreational usage of water bodies (Rudman et al., 2017). Global warming and ongoing nutrient input are predicted to deteriorate water quality and negatively affect ecosystem services of lakes and ponds (Huisman et al., 2018; Rudman et al., 2017), which increases the need for succesful lake management. One tool frequently used in lake management is food chain manipulation, which aims at manipulating the interaction of Daphnia and fish (Jeppesen et al., 2017; Peretyatko et al., 2012; Søndergaard et al., 2017). However, at the molecular level this interaction is not fully understood unless the chemical nature of the fish kairomone is disclosed. Earlier we have shown that the release of the DVM-inducing kairomone does not depend on prior feeding of fish (Loose et al., 1993). The kairomone can be extracted from fish incubation water by lipophilic solid phase extraction, and we have characterized it as a low molecular weight compound carrying a hydroxyl group and a negative charge (Loose et al., 1993; von Elert and Pohnert, 2000; von Elert and Loose, 1996). However, the exact chemical identity of the fish kairomone remained unknown. Here, we use the microcrustean Daphnia, which has become a model organism for the induction of DVM in response to fish (Lampert, 2006; Miner et al., 2012), to identify the yet unknown kairomone.

In order to ensure identification of the major infochemical, we used a bioassay-guided approach. DVM was assessed using a well-established indoor setup in which daytime residence depth in a temperature stratified water column is determined as a proxy for DVM of Daphnia (Brzeziński and von Elert, 2015; Loose et al., 1993; von Elert and Pohnert, 2000). It has earlier been shown that the DVM-inducing activity of fish incubation water can be efficiently extracted by lipophilic solid-phase extraction, whereas solid-phase extracts of control water were not active (von Elert and Loose, 1996). We followed the activity in such an extract of fish incubation water (EFI) of roach (Rutilus rutilus, Cyprinidae) through separation by HPLC and by investigating fractions that cover the whole chromatogram. EFI was found to be active, as it induced a significant shift in the daytime residence depth of Daphnia. Fractionation of EFI by HPLC yielded six fractions (Figure 1A), of which only fraction three proved to induce DVM (Figure 1B, Figure 1—source data 1).

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Figure 1—source data 1

Temperature profile of the experimental tubes.

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Figure 1—source data 2

Response of Daphnia to HPLC fractions.

Statistical analysis of mean daytime residence depth of Daphnia magna in response to different HPLC-fractions (Frac 1 - Frac 6) of extracted fish incubation water (EFI) as shown in Figure 1B. Significantly different pairwise comparisons are given in red, n.s.: not significant.

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Since the kairomone has been shown to be an anion (von Elert and Loose, 1996), LC high-resolution electrospray mass spectrometry (HR-ESI-MS) was performed in the negative ionization mode. Mass data extracted from the time window corresponding to the active fraction 3 (11–14 min), indicated that in this active fraction the most abundant ion had a m/z of 531.29993 corresponding to the deprotonated molecule [M– H]^–, which led to M_calc. = m/z 532.3070 (Figure 2A). The collision-induced fragmentation of [M– H]^– resulted in the detection of the precursor ion and a product ion with a mass of m/z 96.95996 (Figure 2B) corresponding to the monoisotopic mass of hydrogen sulfate (HSO₄^–_calc=m/z 96.96010, ∆ = –1.44 ppm), thus indicating the presence of a sulfate group. The tool sCLIPS included in the software MassWorks (cerno BIOSCIENCE) was used to predict the corresponding sum formula of the detected molecule based on the detected peak of its monoisotopic mass as well as its isotope pattern. The predicted sum formula for [M-H]^- was C₂₇H₄₈O₈S. A data base search using the platform PubChem yielded as best hit cyprinol sulfate (CPS), a known bile compound of fish (Hagey et al., 2010), as a candidate compound for the DVM-inducing activity. This finding was well in accordance with the detected sulfate group.

Figure 2

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Subsequent search for other known bile compounds of fish in the active fraction three revealed the presence of taurochenodeoxycholic acid (TCDCA, Figure 2A, insert, [M-H]^-=m/z 498.28981, C₂₄H₄₄NO₆S, M_calc = m/z 499.28981, ∆=1.8 ppm).

As CPS and TCDCA are known constituents of fish bile (Hagey et al., 2010), we tested bile, which was obtained from the gallbladder of common carp (Cyprinus carpio, Cyprinidae) and rainbow trout (Oncorhynchus mykiss, Salmonidae) for DVM induction in Daphnia. Dilutions of extracted bile of both species corresponding to similar CPS concentrations as found in EFI (carp: 1 and 2 nM, trout: 0.4 and 3.9 nM, EFI: 1 nM) proved to induce DVM with amplitudes that were statistically not distinguishable from those induced by EFI (Figure 3—figure supplement 2 and Figure 3—figure supplement 2—source data 1).

When we compared chromatograms of EFI and the fish bile samples, identical retention times, high-resolution m/z ratios and fragmentation patterns after MS-MS confirmed that α-CPS and TCDCA were also present in carp bile and trout bile (Figure 3, Figure 3—figure supplements 1 and 2). It is well known, that 5α-cyprinol sulfate (α-CPS) constitutes the major bile compound in cyprinid fish (Hagey et al., 2010). Since it is not commercially available, we have isolated α-CPS on a semi-preparative scale from gallbladder of common carp (Cyprinidae) and determined its structure by NMR to be α-CPS in a previous study (Hahn et al., 2018). Hence we conclude that m/z 531.29986 indicates the presence of α-CPS in EFI. The chemical identity of α-CPS and TCDCA was further confirmed by chromatography of reference compounds, which showed retention times and high-resolution m/z values that matched those in the chromatogram of EFI (Figure 3). We conclude that the major constituent of the only active fraction in EFI was the bile salt α-CPS. One further abundant bile salt in this fraction was TCDCA. While the ion detected at 2,04 min is of unknown identity (Figure 3C), we speculate that the second peak in the EIC of m/z = 531.29986 at 2.38 min (Figure 3D) is the isomer β-cyprinol sulfate.

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α-CPS isolated from bile of common carp was used for dose response experiments for the induction of DVM (Figure 4) after checking its purity (Figure 4—figure supplements 1 and 2). α-CPS induced the same predator-avoidance behavior as extracted fish incubation water (EFI) at concentrations ≥ 100 pM (Figur 4A, Figure 4—source data 2). TCDCA proved to be active at ≥20 µM only (Figure 4B, Figure 4—source data 3). As a possible microbial degradation product of TCDCA , we further tested chenodeoxycholic acid (Shimada et al., 1969) which proved to be inactive with respect to DVM-induction in concentrations ≤ 25 µM (Figure 4C, Figure 4—source data 4). In other words, Daphnia were five orders of magnitude more sensitive to α-CPS than to TCDCA, while no DVM induction was found in response to chenodeoxycholic acid (CDCA), the deconjugated form of TCDCA.

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Figure 4—source data 1

Effects of extracted fish incubation water (EFI) and of increasing concentrations of selected bile salts on diel vertical migration.

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Figure 4—source data 2

Response of Daphnia to 5α-cyprinol sulfate.

Statistical analysis of mean daytime residence depth of Daphnia magna in response to different concentrations of 5α-cyprinol sulfate (5α-CPS) as shown in Figure 4A. Significantly different pairwise comparisons are given in red, n.s.: not significant.

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Figure 4—source data 3

Response of Daphnia to 5α-cyprinol sulfate.

Statistical analysis of mean daytime residence depth of Daphnia magna in response to different concentrations of taurochenodeoxycholic acid (TCDCA) as shown in Figure 4B. Significantly different pairwise comparisons are given in red, n.s.: not significant.

https://doi.org/10.7554/eLife.44791.019

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Figure 4—source data 4

Response of Daphnia to chenodeoxycholic acid (CDCA).

Statistical analysis of mean daytime residence depth of Daphnia magna in response to different concentrations of chenodeoxycholic acid (CDCA) as shown in Figure 4C). Significantly different pairwise comparisons are given in red, n.s.: not significant.

https://doi.org/10.7554/eLife.44791.020

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We quantified α-CPS and TCDCA in extracted fish incubation water (EFI, Figure 4—figure supplement 3). As 20 µl of EFI are derived from 1 L of fish incubation water, this volume was dissolved per liter to obtain biologically active water in the bioassay. The actual concentration of α-CPS in biologically active water was 1.03 ± 0.08 nM (mean ± SD, n = 3) and that of TCDCA was 0.14 ± 0.01 nM (mean ± SD, n = 3). Hence the concentration of α-CPS was 7.5-fold higher than that of TCDCA. This concentration of α-CPS in biologically active water clearly exceeded the threshold concentration for biological activity of 100 pM, whereas TCDCA was present in concentrations that were more than five orders of magnitude below the activity threshold concentration of 20 µM. We therefore conclude that α-CPS is the only tested bile salt that is relevant for the induction of DVM in Daphnia in response to fish.

We identified an infochemical that Daphnia uses to perceive the risk of being preyed upon by planktivorous fish. We show that the induction of DVM in Daphnia is dependent on a particular bile compound from fish, that is 5α-cyprinol sulfate (α-CPS), which is active already at a concentration of 100 pM. The identification of α-CPS is the result of a bioassay-guided approach in which we have targeted the main activity throughout all purification steps. Hence, α-CPS constitutes the major activity in fish incubation water. Although another bile compound (TCDCA) was found in the active fraction obtained by HPLC, only α-CPS was present in sufficiently high concentrations to be biologically active. This is due to two factors: (i) Daphnia is five orders of magnitude more sensitive to α-CPS than to TCDCA and (ii) the concentration of α-CPS in extracted fish incubation water is approximately sevenfold higher than that of TCDCA. This substantially higher concentration of α-CPS is well in accordance with the findings that α-CPS constitutes the major bile salt in cyprinid bile (Hofmann et al., 2010).

Concerning the discussion of the estimated threshold concentration of α-CPS for DVM induction one methodological detail has to be considered. α-CPS present in EFI was quantified as equivalents of cholesteryl sulfate, since there has not been enough material of α-CPS to conduct an absolute gravimetric quantification. The quantification of α-CPS by means of a calibration curve of cholesteryl sulfate can however be considered quite accurate since both molecules propably result in comparable detector responses of the ESI-MS for the following reasons: i) both α-CPS and cholesteryl sulfate carry a sulfate group and, without prior ionization, are already negatively charged when reaching the ESI source. Different ionizabilities of both analytes can thus be excluded as source of inaccuracy. ii) The m/z ratios of α-CPS and cholesteryl sulfate are so close to each other (m/z = 465.3039 vs. m/z = 531.2992), that tuning of the mass spectrometer’s ion optics will not differently affect the detectability of either compound. iii) Just like the m/z ratios, the molecular masses of the molecules are comparable as well, so that differences with respect to spray formation in the ESI source are probably of minor importance. In conclusion, it is reasonable to assume that quantification of α-CPS as equivalents of cholesteryl sulfate results in minor inaccuracies only.

α-CPS matches perfectly the previously published chemical characteristics for the DVM-inducing fish kairomone of roach (Rutilus rutilus) and other cyprinid fishes (Loose et al., 1993; von Elert and Loose, 1996). Its molecular mass is close to 500 Dalton, it contains hydroxyl and no amino groups, has a strong negative charge and, as predicted, α-CPS is free of olefinic bonds. The anionic character and the hydroxyl groups make α-CPS a good infochemical in water, as they render the molecule water soluble so that it can well diffuse after release by the predator.

α-CPS, a sulfated bile alcohol, belongs to the bile salts, which are metabolites of cholesterol in vertebrates with the primary function to emulsify dietary fats and to facilitate their intestinal absorption (Maldonado-Valderrama et al., 2011). Although bile salts are an essential component of the enterohepatic circulation, fish excrete bile salts via the intestine, the gills and the urinary tract (Buchinger et al., 2014). Excreted fish bile salts are often highly water soluble due to conjugation with a sulfate (in case of bile alcohols), or with taurine (in case of bile acids). Furthermore, bile salts are generally stable as they must be resistant to digestion within an organism, which makes conjugated bile salts ideal infochemicals. Corroborating results for other bile salts (Zhang et al., 2001), we here demonstrate the release of α-CPS by starved fish. Hence, the induction of DVM by fish does not require successful hunting of fish. The fact that bile salts are essential in fish metabolism explains why, from an evolutionary perspective, fish have not stopped to release bile salts despite its disadvantage for the emitter organism.

The DVM-inducing kairomone that we report here is to our knowledge the first identification of an aquatic kairomone that mediates predator-prey interactions between zooplankton and fish. The other few cases in zooplankton, for which chemical cues have been identified, are interactions of herbivorous zooplankton with its phytoplankton prey (Selander et al., 2015; Uchida et al., 2008) and with an invertebrate predator (Weiss et al., 2018): Copepods were shown to release copepodamides, a class of taurine containing polar lipids, which leads to an increased toxicity in their dinoflagellate prey (Selander et al., 2015); Daphnia have been reported to release an alkylsulfate into the water that induces the formation of protective colonies in the green alga Acutodesmus obliquus (Uchida et al., 2008), and larvae of Chaoborus sp. release fatty acids bound to a particular amino acid, which lead to changes in morphology in Daphnia pulex (Weiss et al., 2018). Among benthic animals a predatory crab has been shown to release two pyridin-metabolites that induce defensive behavior in a prey crab (Poulin et al., 2018). The sterane core of α-CPS renders it partly lipophilic, and causes together with the sulfate group the overall amphipathic nature of α-CPS. Sulfate or sulfonium groups are present in several of the compounds known in chemical communication of zooplankton (Selander et al., 2015; Uchida et al., 2008) and as well in the sex pheromone of lamprey (Li et al., 2002).

We accomplished the identification of α-CPS as the DVM-inducing kairomone using incubation water from Rutilus rutilus (Cyprinidae). The family of Cyprinidae is with more than 2000 species the largest family of fishes, and dominates freshwater habitats around the world with the exception of South America and Australia, and a considerable number of species is found in brackish water (Hastings et al., 2015). In line with the high diversity of cyprinid fish, incubation water of many cyprinid species has been demonstrated to induce DVM in Daphnia (Lass and Spaak, 2003), and we have shown that the chemical characteristics of the kairomone are identical among different cyprinid species (von Elert and Loose, 1996) which matches the finding that α-CPS is the dominant bile salt in the Cypriniformes (Hagey et al., 2010).

We further demonstrate that the induction of DVM by TCDCA, a representative for taurine-conjugated C₂₄ bile acids, required substantially higher concentrations (≥20 µM, which equals ≥10 mg dissolved organic carbon/L) than induction by α-CPS. The observation that free bile acids occur in fish feces suggests a low degree of bacterial deconjugation of conjugated bile acids by gut bacteria (Philipp, 2011). However, such bacterial deconjugation of TCDCA would not release DVM-inducing activity, as the resulting free C₂₄ bile acid CDCA was even less active than TCDCA. Neither this finding nor the fact that α-CPS, a fish metabolite that has not been microbially modified, constitutes the major kairomone in fish incubation water support the earlier suggestion that bacteria are involved in the production of the kairomone (Ringelberg and Van Gool, 1998).

As well non-cyprinid fish species like perch, stickleback (Perciformes) and pike (Esociformes) induce DVM in Daphnia (von Elert and Pohnert, 2000), and the chemical characteristics of kairomones from pike and stickleback match those of cyprinids (von Elert and Pohnert, 2000), which suggests that the kairomones of non-cyprinid and cyprinid species are similar and perhaps identical. However, a general pattern that emerges from a comprehensive analysis of bile salt patterns in fish indicates that α-CPS is confined to Cypriniformes and absent in the fish orders Perciformes, Esociformes and Salmoniformes. Yet, we here demonstrate the presence of α-CPS in bile of rainbow trout (Oncorhynchus mykiss), a representative of Salmoniformes. Still, this finding is in accordance with the general bile salt pattern in fish, as this pattern considers only bile salt types present at 5% or greater of the bile salt pool (Hagey et al., 2010). Furthermore, the authors argue, that the production of bile alcohols such as α-cyprinol (a C₂₇ bile alcohol) and their conjugation to sulfate is regarded as an evolutionarily ancient bile salt profile (Hagey et al., 2010). All evolutionarily more recent bile salt patterns of fish seem to have evolved from the putatively ancestral pattern of C₂₇ bile alcohol production by subsequent enzymatic modifications of them (Hagey et al., 2010; Hofmann et al., 2010). In line with this bile of many ray-finned fish species still contains traces of the biosynthetic precursor C₂₇ bile alcohol though their bile is dominated by conjugated C₂₄ bile acids (Hagey et al., 2010). We deduce that even in fish orders with a more recent bile acid pattern, α-CPS may be present in traces (i.e. <5%) as we have demonstrated for salmon, although this remains to be demonstrated for example for stickleback and Perciformes.

Our findings thus suggest that Daphnia evolution has selected for a high sensitivity to the evolutionarily oldest bile product of fish, that is α-CPS, and that this has proven to be an evolutionarily stable strategy as evolutionarily more recent fish bile patterns still contain traces of α-CPS. Thus, by sensing a single bile compound only, Daphnia are able to perceive the presence of fish across very different orders (Hagey et al., 2010). Future research will have to prove that 5α-CPS or other, hithertounidentified compounds, serve as the DVM-inducing kairomone as well in non-cyprinid fish orders.

The identification of α-CPS as the DVM-inducing kairomone in Daphnia allows for the assessment of its in situ concentration in space and time and thus to understand trait-variation in Daphnia and within-lake variations of DVM-amplitudes. The finding that a bile salt from fish serves as an infochemical might stimulate testing for a role of these compounds in the marine environment, where similar patterns of DVM of zooplankton are common. Still, although cessation of DVM in marine copepods in the absence of fish has been shown (Bollens and Frost, 1991), its induction in the presence of fish could not be demonstrated (Bollens and Frost, 1991). Similarly, a potential role of bile salts from fish in other anti-fish defenses in freshwater invertebrates remains to be tested, for example in changes in Daphnia life-history (Stibor, 1992) or morphology (Tollrian, 1994), in the reduced pigmentation of copepods in the presence of fish (Hansson, 2000) or in mediating effects of fish on the oviposition site of female Chaoborus (Berendonk, 1999). Knowing the kairomone now allows for identification of the α-CPS binding receptor in Daphnia in order to understand the rapid evolution of DVM in response to the absence/presence of fish (Cousyn et al., 2001).

All data generated or analyzed during this study are included in the manuscript and supporting files. Source data files have been provided for Figure 1, Figure 1—figure supplement 2, Figure 4, Figure 3—figure supplement 2, and Figure 4—figure supplement 6.

1. 1. Hahn M
   2. Effertz C
   3. Bigler L
   4. von Elert E

   (2019) Dryad Digital Repository

   Data from: A bile salt from fish induces diel vertical migration in zooplankton.

   https://doi.org/10.5061/dryad.5d69g86

1. 1. Abrams PA

   (1984) Foraging time optimization and interactions in food webs

   The American Naturalist 124:80–96.

   https://doi.org/10.1086/284253

   • Google Scholar
2. 1. Berendonk TU

   (1999) Influence of fish kairomones on the ovipositing behavior of Chaoborus imagines

   Limnology and Oceanography 44:454–458.

   https://doi.org/10.4319/lo.1999.44.2.0454

   • Google Scholar
3. 1. Bjærke O
   2. Andersen T
   3. Titelman J

   (2014) Predator chemical cues increase growth and alter development in nauplii of a marine copepod

   Marine Ecology Progress Series 510:15–24.

   https://doi.org/10.3354/meps10918

   • Google Scholar
4. 1. Bollens SM
   2. Frost BW

   (1991) Diel vertical migration in zooplankton: rapid individual response to predators

   Journal of Plankton Research 13:1359–1365.

   https://doi.org/10.1093/plankt/13.6.1359

   • Google Scholar
5. Book

   1. Brönmark C
   2. Hansson L-A

   (2012)

   Chemical Ecology in Aquatic Systems

   Oxford University Press.

   • Google Scholar
6. 1. Brzeziński T
   2. von Elert E

   (2015) Predator evasion in zooplankton is suppressed by polyunsaturated fatty acid limitation

   Oecologia 179:687–697.

   https://doi.org/10.1007/s00442-015-3405-4

   • PubMed
   • Google Scholar
7. 1. Buchinger TJ
   2. Li W
   3. Johnson NS

   (2014) Bile salts as semiochemicals in fish

   Chemical Senses 39:647–654.

   https://doi.org/10.1093/chemse/bju039

   • PubMed
   • Google Scholar
8. 1. Cousyn C
   2. De Meester L
   3. Colbourne JK
   4. Brendonck L
   5. Verschuren D
   6. Volckaert F

   (2001) Rapid, local adaptation of zooplankton behavior to changes in predation pressure in the absence of neutral genetic changes

   PNAS 98:6256–6260.

   https://doi.org/10.1073/pnas.111606798

   • PubMed
   • Google Scholar
9. 1. Denton JE
   2. Yousef MK
   3. Yousef IM
   4. Kuksis

   (1974) Bile acid composition of rainbow trout, Salmo gairdneri

   Lipids 9:945–951.

   https://doi.org/10.1007/BF02533816

   • PubMed
   • Google Scholar
10. 1. Dodson S

    (1988) The ecological role of chemical stimuli for the zooplankton: Predator-avoidance behavior in Daphnia

    Limnology and Oceanography 33:1431–1439.

    https://doi.org/10.4319/lo.1988.33.6_part_2.1431

    • Google Scholar
11. 1. Effertz C
    2. von Elert E

    (2014) Light intensity controls anti-predator defences in Daphnia: the suppression of life-history changes

    Proceedings of the Royal Society B: Biological Sciences 281:20133250.

    https://doi.org/10.1098/rspb.2013.3250

    • PubMed
    • Google Scholar
12. 1. Ford AT
    2. Goheen JR
    3. Otieno TO
    4. Bidner L
    5. Isbell LA
    6. Palmer TM
    7. Ward D
    8. Woodroffe R
    9. Pringle RM

    (2014) Large carnivores make savanna tree communities less thorny

    Science 346:346–349.

    https://doi.org/10.1126/science.1252753

    • PubMed
    • Google Scholar
13. 1. Gliwicz MZ

    (1986) Predation and the evolution of vertical migration in zooplankton

    Nature 320:746–748.

    https://doi.org/10.1038/320746a0

    • Google Scholar
14. 1. Hagey LR
    2. Møller PR
    3. Hofmann AF
    4. Krasowski MD

    (2010) Diversity of bile salts in fish and amphibians: evolution of a complex biochemical pathway

    Physiological and Biochemical Zoology 83:308–321.

    https://doi.org/10.1086/649966

    • PubMed
    • Google Scholar
15. 1. Hahn M
    2. von Elert E
    3. Bigler L
    4. Díaz Hernández MD
    5. Schloerer NE

    (2018) 5α-Cyprinol sulfate: Complete NMR assignment and revision of earlier published data, including the submission of a computer-readable assignment in NMReDATA format

    Magnetic Resonance in Chemistry 56:1201–1207.

    https://doi.org/10.1002/mrc.4782

    • PubMed
    • Google Scholar
16. 1. Hansson LA

    (2000) Induced pigmentation in zooplankton: a trade-off between threats from predation and ultraviolet radiation

    Proceedings of the Royal Society of London. Series B: Biological Sciences 267:2327–2331.

    https://doi.org/10.1098/rspb.2000.1287

    • PubMed
    • Google Scholar
17. Book

    1. Hastings PA
    2. Walker HJ
    3. Galland GR

    (2015)

    Fishes: A Guide to Their Diversity

    University of California Press.

    • Google Scholar
18. 1. Haupt F
    2. Stockenreiter M
    3. Reichwaldt ES
    4. Baumgartner M
    5. Lampert W
    6. Boersma M
    7. Stibor H

    (2010) Upward phosphorus transport by Daphnia diel vertical migration

    Limnology and Oceanography 55:529–534.

    https://doi.org/10.4319/lo.2010.55.2.0529

    • Google Scholar
19. 1. Hays GC

    (2003) A review of the adaptive significance and ecosystem consequences of zooplankton diel vertical migrations

    Hydrobiologia 503:163–170.

    https://doi.org/10.1023/B:HYDR.0000008476.23617.b0

    • Google Scholar
20. 1. Heithaus MR
    2. Wirsing AJ
    3. Thomson JA
    4. Burkholder DA

    (2008) A review of lethal and non-lethal effects of predators on adult marine turtles

    Journal of Experimental Marine Biology and Ecology 356:43–51.

    https://doi.org/10.1016/j.jembe.2007.12.013

    • Google Scholar
21. 1. Hofmann AF
    2. Hagey LR
    3. Krasowski MD

    (2010) Bile salts of vertebrates: structural variation and possible evolutionary significance

    Journal of Lipid Research 51:226–246.

    https://doi.org/10.1194/jlr.R000042

    • PubMed
    • Google Scholar
22. 1. Huisman J
    2. Codd GA
    3. Paerl HW
    4. Ibelings BW
    5. Verspagen JMH
    6. Visser PM

    (2018) Cyanobacterial blooms

    Nature Reviews Microbiology 16:471–483.

    https://doi.org/10.1038/s41579-018-0040-1

    • PubMed
    • Google Scholar
23. 1. Jeppesen E
    2. Søndergaard M
    3. Liu Z

    (2017) Lake restoration and management in a climate change perspective: an introduction

    Water 9:122.

    https://doi.org/10.3390/w9020122

    • Google Scholar
24. 1. Kats LB
    2. Dill LM

    (1998) The scent of death: Chemosensory assessment of predation risk by prey animals

    Écoscience 5:361–394.

    https://doi.org/10.1080/11956860.1998.11682468

    • Google Scholar
25. 1. Lampert W

    (1991) The dynamics of Daphnia magna in a shallow lake

    SIL Proceedings, 1922-2010 24:795–798.

    https://doi.org/10.1080/03680770.1989.11898852

    • Google Scholar
26. 1. Lampert W

    (1993)

    Ultimate causes for diel vertical migration of zooplankton: new evidence for the predator avoidance hypothesis

    Archiv für Hydrobiologie Beiheft/Ergebnisse der Limnologie 39:79–88.

    • Google Scholar
27. 1. Lampert W

    (2006)

    Daphnia: model herbivore, predator and prey

    Polish Journal of Ecology 54:607–620.

    • Google Scholar
28. 1. Lass S
    2. Spaak P

    (2003) Chemically induced anti-predator defences in plankton: a review

    Hydrobiologia 491:221–239.

    https://doi.org/10.1023/A:1024487804497

    • Google Scholar
29. 1. Li W
    2. Scott AP
    3. Siefkes MJ
    4. Yan H
    5. Liu Q
    6. Yun SS
    7. Gage DA
    8. Yun, DA Gage S-S

    (2002) Bile Acid secreted by male sea lamprey that acts as a sex pheromone

    Science 296:138–141.

    https://doi.org/10.1126/science.1067797

    • PubMed
    • Google Scholar
30. 1. Lima SL

    (1998) Nonlethal effects in the ecology of predator-prey interactions

    BioScience 48:25–34.

    https://doi.org/10.2307/1313225

    • Google Scholar
31. 1. Loose CJ
    2. Von Elert E
    3. Dawidowicz P

    (1993)

    Chemically-induced diel vertical migration in Daphnia: a new bioassay for kairomones exuded by fish

    Archiv Für Hydrobiologie 126:329–337.

    • Google Scholar
32. 1. Loose CJ
    2. Dawidowicz P

    (1994) Trade-offs in diel vertical migration by zooplankton: the costs of predator avoidance

    Ecology 75:2255–2263.

    https://doi.org/10.2307/1940881

    • Google Scholar
33. 1. Maldonado-Valderrama J
    2. Wilde P
    3. Macierzanka A
    4. Mackie A

    (2011) The role of bile salts in digestion

    Advances in Colloid and Interface Science 165:36–46.

    https://doi.org/10.1016/j.cis.2010.12.002

    • PubMed
    • Google Scholar
34. 1. Miner BE
    2. De Meester L
    3. Pfrender ME
    4. Lampert W
    5. Hairston NG

    (2012) Linking genes to communities and ecosystems: Daphnia as an ecogenomic model

    Proceedings of the Royal Society B: Biological Sciences 279:1873–1882.

    https://doi.org/10.1098/rspb.2011.2404

    • PubMed
    • Google Scholar
35. 1. Moll RJ
    2. Redilla KM
    3. Mudumba T
    4. Muneza AB
    5. Gray SM
    6. Abade L
    7. Hayward MW
    8. Millspaugh JJ
    9. Montgomery RA

    (2017) The many faces of fear: a synthesis of the methodological variation in characterizing predation risk

    Journal of Animal Ecology 86:749–765.

    https://doi.org/10.1111/1365-2656.12680

    • PubMed
    • Google Scholar
36. 1. Neill WE

    (1990) Induced vertical migration in copepods as a defence against invertebrate predation

    Nature 345:524–526.

    https://doi.org/10.1038/345524a0

    • Google Scholar
37. 1. Peretyatko A
    2. Teissier S
    3. De Backer S
    4. Triest L

    (2012) Biomanipulation of hypereutrophic ponds: when it works and why it fails

    Environmental Monitoring and Assessment 184:1517–1531.

    https://doi.org/10.1007/s10661-011-2057-z

    • PubMed
    • Google Scholar
38. 1. Philipp B

    (2011) Bacterial degradation of bile salts

    Applied Microbiology and Biotechnology 89:903–915.

    https://doi.org/10.1007/s00253-010-2998-0

    • PubMed
    • Google Scholar
39. 1. Pohnert G
    2. Steinke M
    3. Tollrian R

    (2007) Chemical cues, defence metabolites and the shaping of pelagic interspecific interactions

    Trends in Ecology & Evolution 22:198–204.

    https://doi.org/10.1016/j.tree.2007.01.005

    • PubMed
    • Google Scholar
40. 1. Poulin RX
    2. Lavoie S
    3. Siegel K
    4. Gaul DA
    5. Weissburg MJ
    6. Kubanek J

    (2018) Chemical encoding of risk perception and predator detection among estuarine invertebrates

    PNAS 115:662–667.

    https://doi.org/10.1073/pnas.1713901115

    • PubMed
    • Google Scholar
41. 1. Preisser EL
    2. Bolnick DI
    3. Benard MF

    (2005) Scared to death? the effects of intimidation and consumption in predator-prey interactions

    Ecology 86:501–509.

    https://doi.org/10.1890/04-0719

    • Google Scholar
42. 1. Reichwaldt ES
    2. Stibor H

    (2005) The impact of diel vertical migration of Daphnia on phytoplankton dynamics

    Oecologia 146:50–56.

    https://doi.org/10.1007/s00442-005-0176-3

    • PubMed
    • Google Scholar
43. 1. Rhode SC
    2. Pawlowski M
    3. Tollrian R

    (2001) The impact of ultraviolet radiation on the vertical distribution of zooplankton of the genus Daphnia

    Nature 412:69–72.

    https://doi.org/10.1038/35083567

    • PubMed
    • Google Scholar
44. 1. Ringelberg J

    (1999) The photobehaviour of Daphnia spp. as a model to explain diel vertical migration in zooplankton

    Biological Reviews of the Cambridge Philosophical Society 74:397–423.

    https://doi.org/10.1017/S0006323199005381

    • Google Scholar
45. 1. Ringelberg J
    2. Van Gool E

    (1998) Do bacteria, not fish, produce ‘fish kairomone’?

    Journal of Plankton Research 20:1847–1852.

    https://doi.org/10.1093/plankt/20.9.1847

    • Google Scholar
46. 1. Rudman SM
    2. Kreitzman M
    3. Chan KMA
    4. Schluter D

    (2017) Evosystem services: rapid evolution and the provision of ecosystem services

    Trends in Ecology & Evolution 32:403–415.

    https://doi.org/10.1016/j.tree.2017.02.019

    • PubMed
    • Google Scholar
47. 1. Selander E
    2. Kubanek J
    3. Hamberg M
    4. Andersson MX
    5. Cervin G
    6. Pavia H

    (2015) Predator lipids induce paralytic shellfish toxins in bloom-forming algae

    PNAS 112:6395–6400.

    https://doi.org/10.1073/pnas.1420154112

    • PubMed
    • Google Scholar
48. 1. Shimada K
    2. Bricknell KS
    3. Finegold SM

    (1969) Deconjugation of bile acids by intestinal bacteria: review of literature and additional studies

    Journal of Infectious Diseases 119:273–281.

    https://doi.org/10.1093/infdis/119.3.273

    • PubMed
    • Google Scholar
49. 1. Sih A

    (1980) Optimal behavior: can foragers balance two conflicting demands?

    Science 210:1041–1043.

    https://doi.org/10.1126/science.210.4473.1041

    • PubMed
    • Google Scholar
50. 1. Søndergaard M
    2. Lauridsen T
    3. Johansson L
    4. Jeppesen E

    (2017) Repeated fish removal to restore lakes: case study of Lake Væng, Denmark—two biomanipulations during 30 years of monitoring

    Water 9:43.

    https://doi.org/10.3390/w9010043

    • Google Scholar
51. 1. Stibor H

    (1992) Predator induced life-history shifts in a freshwater cladoceran

    Oecologia 92:162–165.

    https://doi.org/10.1007/BF00317358

    • Google Scholar
52. 1. Stich H-B
    2. Lampert W

    (1981) Predator evasion as an explanation of diurnal vertical migration by zooplankton

    Nature 293:396–398.

    https://doi.org/10.1038/293396a0

    • Google Scholar
53. 1. Tollrian R

    (1994)

    Fish-kairomone induced morphological changes in Daphnia lumholtzi (SARS)

    Archiv Fur Hydrobiologie 130:69–75.

    • Google Scholar
54. 1. Turner AM
    2. Bernot RJ
    3. Boes CM

    (2000) Chemical cues modify species interactions: the ecological consequences of predator avoidance by freshwater snails

    Oikos 88:148–158.

    https://doi.org/10.1034/j.1600-0706.2000.880117.x

    • Google Scholar
55. 1. Uchida H
    2. Yasumoto K
    3. Nishigami A
    4. Zweigenbaum JA
    5. Kusumi T
    6. Ooi T

    (2008) Time-of-Flight LC/MS identification and confirmation of a kairomone in Daphnia magna cultured medium

    Bulletin of the Chemical Society of Japan 81:298–300.

    https://doi.org/10.1246/bcsj.81.298

    • Google Scholar
56. 1. Van Gool E
    2. Ringelberg J

    (2002) Relationship between fish kairomone concentration in a lake and phototactic swimming by Daphnia

    Journal of Plankton Research 24:713–721.

    https://doi.org/10.1093/plankt/24.7.713

    • Google Scholar
57. 1. von Elert E
    2. Loose CJ

    (1996) Predator-induced diel vertical migration in Daphnia: enrichment and preliminary chemical characterization of a kairomone exuded by fish

    Journal of Chemical Ecology 22:885–895.

    https://doi.org/10.1007/BF02029942

    • PubMed
    • Google Scholar
58. 1. von Elert E
    2. Pohnert G

    (2000) Predator specificity of kairomones in diel vertical migration of Daphnia: a chemical approach

    Oikos 88:119–128.

    https://doi.org/10.1034/j.1600-0706.2000.880114.x

    • Google Scholar
59. 1. Weiss LC
    2. Albada B
    3. Becker SM
    4. Meckelmann SW
    5. Klein J
    6. Meyer M
    7. Schmitz OJ
    8. Sommer U
    9. Leo M
    10. Zagermann J
    11. Metzler-Nolte N
    12. Tollrian R

    (2018) Identification of Chaoborus kairomone chemicals that induce defences in Daphnia

    Nature Chemical Biology 14:1133–1139.

    https://doi.org/10.1038/s41589-018-0164-7

    • PubMed
    • Google Scholar
60. 1. Werner EE
    2. Peacor SD

    (2003) A review of trait-mediated indirect interactions in ecological communities

    Ecology 84:1083–1100.

    https://doi.org/10.1890/0012-9658(2003)084[1083:AROTII]2.0.CO;2

    • Google Scholar
61. 1. Williamson CE
    2. Fischer JM
    3. Bollens SM
    4. Overholt EP
    5. Breckenridge JK

    (2011) Toward a more comprehensive theory of zooplankton diel vertical migration: Integrating ultraviolet radiation and water transparency into the biotic paradigm

    Limnology and Oceanography 56:1603–1623.

    https://doi.org/10.4319/lo.2011.56.5.1603

    • Google Scholar
62. 1. Zhang C
    2. Brown SB
    3. Hara TJ

    (2001) Biochemical and physiological evidence that bile acids produced and released by lake char (Salvelinus namaycush) function as chemical signals

    Journal of Comparative Physiology B: Biochemical, Systemic, and Environmental Physiology 171:161–171.

    https://doi.org/10.1007/s003600000170

    • PubMed
    • Google Scholar

Thank you for submitting your article "A bile salt from fish induces diel vertical migration in zooplankton" for consideration by eLife. Your article has been reviewed by three peer reviewers, including Georg Pohnert as the Reviewing Editor and Reviewer #1, and the evaluation has been overseen by Ian Baldwin as the Senior Editor.

The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.

Summary:

The concept of a compound that has to be released by fish due to their metabolic activity and that signals their presence to few millimeter sized Daphnia who make avoidance reactions is intriguing. The manuscript describes therefore a breakthrough in aquatic kairomone research and clearly demonstrates the activity of a fish bile salt to induce diel vertical migration in Daphnia. It answers a long-standing question and opens up new perspectives in kairomone research. The knowledge about the active principle will further open up new perspectives in environmental and ecological research.

Essential revisions:

All reviewers agreed that the manuscript describes an important progress in the field and a solid piece of chemical ecology. However, several concerns about the presentation of the work were raised.

As can be seen in the detailed comments below all reviewers recommend a substantial focus of the discussion on core-results of the paper. Further, two reviewers recommend that the quantification of the kairomone should be better documented.

The title could be more precise; the compound that was elucidated could be mentioned – especially since a specific activity was observed.

The manuscript is already in itself convincing, but the discussion about anthropogenic infodisruption (Abstract and Discussion) seems to be farfetched. The specificity of the response and the discussion about amounts of potential info disruptors required to triggers a response makes it a quite speculative discussion. The core result is very strong; there is no need to extend it into speculation. I would suggest deleting the part of the Discussion paragraphs five and seven. Also, reviewer 2 states clearly "The infodisruption part is a bit overstated. If TCDCA from anthropogenic sources is really released with sewage in such high concentrations, it might induce DVM in the vicinity of the inflow. However usually it will be diluted and probably most lakes where sewage is flowing in contain fish anyhow. Thus, the proposed ‘far-reaching implications for ecosystem functioning and conservation management’ are not obvious."

Further in many places the authors discuss DVM in general, leading to the impression that 5α-CPS is, or might be, responsible for DVM worldwide. This is most probably not true. There is no indication that DVM in marine environments is chemically induced at all. Bollens and Frost tested chemical cues from fish in enclosures and did not find an induction of DVM. While it is widely accepted that DVM is an anti-predator strategy, behavioral plasticity has not been shown in the marine environment. Furthermore, there are no cyprinids in most marine environments. To emphasize my point, this does not mean that DVM in the marine environment is not induced by 5α-CPS – it simply needs to be shown.

The authors suggest that 5α-CPS is the only relevant fish kairomone and their results indeed indicate that also rainbow trout produce this kairomone. However, Hagey et al., 2010, presented a number of orders which do not produce 5α-CPS, including Perciformes and Esociformes, but also Salmoniformes. Perciformes and Esociformes have been used to induce depth selection behavior, e.g., Ringelberg and van Gool, 1998, and the authors induced with Esox lucius in an earlier study. Thus, there seems to be some deviating results which require some discussion. It might simply indicate that some clarification is necessary, or it might call for future studies. The authors discuss effects on the marine carbon pump and suggest that 5α-CPS is the responsible cue. This is overstating.

Quantification is certainly the weakest point of the study: First normalization to cholesteryl sulfate and CPS would require a response factor of both analytes or better a calibration curve. The sentence “As 20 µL […]” suggests that the concentration of DPS was determined by bioassays not be analytical methods? Given the experimental I thought quantification with normalization to cholesterol sulfate was done. Also, reviewer 2 states: “It is necessary to present the concentrations clearer. E.g., the size of the fish should be mention as the release of the kairomone might be correlated to fish size. How large where the fish for gall bladder extraction? How much bile has been extracted in Rainbow trout?”

The reviewers also discussed the validity of the term bioassay guided fractionation: The approach used is known as "bioassay-guided fractionation", by which compounds purified from fish exudates were tested for escape-inducing behavior, resulting in the eventual identification of a single molecule responsible for the observed effect on prey. The manuscript is largely focused on the process of identifying this molecule via a combination of chemical and behavioral experiments. The molecule, 5α-cyprinol sulfate, is a known product of the digestive systems of fish – a logical candidate for a cue that prey might use to sense their predators and respond defensively. Given the fact that the authors just published a paper on this compound and its NMR data makes us wonder if we are not rather dealing with a targeted study confirming the activity of a logical candidate. This would twist the whole presentation but maybe leave a better feeling after reading. The current manuscript represents one such study. The fact that the molecule the authors identified was previously known (albeit present and active at low nanomolar concentrations), makes the chemistry of the study a little less exciting, but the biological implications are still important.

Reviewer 3 is quite critical in this point: The paper is solid and clear, but it lacks the kind of general appeal that expected for publication in eLife. In particular, the Introduction is quite basic, written in a way that is unlikely to draw in strangers to chemical ecology. The Discussion is similarly restricted to similar systems (fish and plankton). The description of the impacts of predation, chemical cues, and predator escape strategies would need broadening and enriching to be appropriate for this kind of general journal. The chemistry-oriented results are not particularly accessible to a general biology readership. As currently presented, the work is more appropriate for a more specialized journal like J. Chem. Ecol. or one committed to publishing works about freshwater ecology such as Limnology and Oceanography. The section of the Discussion related to movement of zooplankton (and thus effects on their own prey, phytoplankton) and resulting impacts on nutrient cycling would be of particular interest to a limnological and oceanographic audience. After a discussion among the reviewers the study was considered to be important and appealing to warrant further consideration of a revised version of the manuscript but the concerns of reviewer 3 should be kept in mind during revision and re-drafting of the Introduction and Discussion.

Introduction section / Discussion paragraph two: The statement “virtually nothing is known about the chemical nature […]" might have been true 10 years ago, however there is substantial progress in the field and while only few compounds have been fully investigated (these should be cited) several studies address the compound classes, functional modes of action etc. involved. This part of the Introduction should be expanded. This is a common notion among the reviewers "The authors suggest that virtually no aquatic kairomone has been identified, ignoring the recent publication of the Chaoborus kairomone – another relevant kairomone for Daphnia with some similarities (Weiss et al., 2018)."

Results second paragraph: The calculation is incorrect. The value 532.29993 would suggest that H has a mass of 1. It is however 1.007 will lead to a calculated mass of 532.30693.

Results second paragraph: Why is a data base search required to determine the sum formula from a high res mass? The software of the instrument can simply calculate this.

In the same paragraph: The step from the high res mass to the structure is not clear. Is the entire process only based on this one MS?

Figure 3: Are there explanations for the peaks at 2.04 and 2.38?

Figure 4: The structures are the major result of the paper – they could be plotted bigger. The stereocenter on the C/D ring carbon of CPS should be indicated. Is there any information about the stereochemistry in the side chain?

Results paragraph five: The negative ionization ESI MS in Figure 4—figure supplement 1 can by no means be seen as a proof of purity. In fact, negative ionization only picks up a fraction of compounds in a mixture and in addition, the MS is not clearly indicating a pure compound. Show at least chromatograms in positive and negative ionization mode if no NMR data are available.

Discussion paragraph six and onwards: The Discussion loses focus. Results from freshwater systems (this paper) are mixed with marine/oceanographic facts and become very speculative. The paper should focus more. Constructing e.g. a story about ocean acidification from the results is not justified.

Also: Salmon louse responses to CPS have to be proven, deduction from an uncharacterized receptor sequence to a DVM response are not warranted. Basically, a speculation is built on a speculation.

Reviewer #2

Some studies are ignored that proved that UV-radiation is also inducing DVM in Daphnia, showing that it is additionally a strategy leading to avoidance of harmful irradiation (see. Rhode et al., 2001 or Leech and Williamson (2001, L and O).

Ringelberg and van Gool, 1998, suggest that bacteria are responsible at a certain step of the kairomone production as addition of an antibiotic prevented depth selection behavior. This might be addressed in the Discussion.

Specific comments:

I suggest changing the title to indicate that currently 5α-CPS has been shown to induce DVM in Daphnia magna and most likely in all daphnids. There is no indication that other genera respond to this kairomone.

"A bile salt from fish induces diel vertical migration in Daphnia"

Essential revisions:

All reviewers agreed that the manuscript describes an important progress in the field and a solid piece of chemical ecology. However, several concerns about the presentation of the work were raised.

As can be seen in the detailed comments below all reviewers recommend a substantial focus of the discussion on core-results of the paper. Further, two reviewers recommend that the quantification of the kairomone should be better documented.

The title could be more precise; the compound that was elucidated could be mentioned – especially since a specific activity was observed.

We have accordingly extended/changed the title into: “5α-cyprinol sulfate, a bile salt from fish induces diel vertical migration in Daphnia” (see also below, response to specific comments from #2).

The manuscript is already in itself convincing, but the discussion about anthropogenic infodisruption (Abstract and Discussion) seems to be farfetched. The specificity of the response and the discussion about amounts of potential info disruptors required to triggers a response makes it a quite speculative discussion. The core result is very strong; there is no need to extend it into speculation. I would suggest deleting the part of the Discussion paragraphs five and seven. Also, reviewer 2 states clearly "The infodisruption part is a bit overstated. If TCDCA from anthropogenic sources is really released with sewage in such high concentrations, it might induce DVM in the vicinity of the inflow. However usually it will be diluted and probably most lakes where sewage is flowing in contain fish anyhow. Thus, the proposed ‘far-reaching implications for ecosystem functioning and conservation management’ are not obvious."

As suggested, we now have removed this aspect from the Discussion and also from the Abstract.

Further in many places the authors discuss DVM in general, leading to the impression that 5α-CPS is, or might be, responsible for DVM worldwide. This is most probably not true. There is no indication that DVM in marine environments is chemically induced at all. Bollens and Frost tested chemical cues from fish in enclosures and did not find an induction of DVM. While it is widely accepted that DVM is an anti-predator strategy, behavioral plasticity has not been shown in the marine environment. Furthermore, there are no cyprinids in most marine environments. To emphasize my point, this does not mean that DVM in the marine environment is not induced by 5α-CPS – it simply needs to be shown.

We fully agree, except for the very minor point that in Bollens and Frost, 1991, behavioural plasticity of the copepods was shown (the cessation of DVM after removal of predators), but, of course, no induction by fish-cues. We are no more referring to DVM on a global scale, but confine the introduction to DVM in Daphnia. In the Introduction we are now stating: “One classical example of behavioural predator avoidance is diel vertical migration (DVM) in the freshwater microcrustacean Daphnia, which play a key role in lakes and ponds, as they are major consumers of planktonic primary producers and important prey for higher trophic levels. DVM is a widespread predator avoidance behavior […]”.

The authors suggest that 5α-CPS is the only relevant fish kairomone and their results indeed indicate that also rainbow trout produce this kairomone. However, Hagey et al., 2010, presented a number of orders which do not produce 5α-CPS, including Perciformes and Esociformes, but also Salmoniformes. Perciformes and Esociformes have been used to induce depth selection behavior, e.g., Ringelberg and van Gool, 1998, and the authors induced with Esox lucius in an earlier study. Thus, there seems to be some deviating results which require some discussion. It might simply indicate that some clarification is necessary, or it might call for future studies. The authors discuss effects on the marine carbon pump and suggest that 5α-CPS is the responsible cue. This is overstating.

We have now excluded any reference to the marine carbon pump. We are now addressing this issue of potential deviations in the Discussion in detail. In short, we argue (i) that the general phylogenetic pattern did not consider bile acids with <5% abundance, (ii) that we have shown that salmon has traces of a-CPS though it should not have according to the general phylogenetic pattern, which (iii) renders it possible that a-CPS serves as DVM-inducing kairomone as well in non-cyprinid fish oders, which (iv) remains to be confirmed by future research (Discussion paragraph eight).

Quantification is certainly the weakest point of the study: First normalization to cholesteryl sulfate and CPS would require a response factor of both analytes or better a calibration curve. The sentence “As 20 µL […]” suggests that the concentration of DPS was determined by bioassays not be analytical methods? Given the experimental I thought quantification with normalization to cholesterol sulfate was done.

α-CPS was enriched from fish incubation water by solid-phase extraction. The extract (EFI) corresponded (concerning the volume) to 50,000 times concentrated fish incubation water (density: 3 fish in 8 L water). Thus dissolving 20µL of this 50,000 times concentrated fish incubation water extract in 1 L corresponded to 1 L of the original non-processed incubation water (ignoring losses during extraction) (subsection “Statistics”). The concentration of α-CPS in the extract (EFI) and (thereby also in the artificially produced fish incubation water: EFI + aged and filtered tap water) have not been determined by bioassay. Instead, α-CPS in EFI was determined analytically by LC-MS using a calibration curve for cholesteryl sulfate in the background/matrix of EFI to exclude effects of ion suppression that might be caused by the complex matrix of EFI. We now point out that we only quantified α-CPS as equivalents of cholesteryl sulfate:

“[…] the concentrations of α-CPS were derived from a calibration curve using the purchasable cholesteryl sulfate (Figure 4—figure supplement 6), whose molecular structure suggests a similar detectability by ESI-MS.”

We further discuss the accuracy of this approach:

“Concerning the discussion of the estimated threshold concentration of α-CPS for DVM induction one methodological detail has to be considered. α-CPS present in EFI was quantified as equivalents of cholesteryl sulfate, since there has not been enough material of α-CPS to conduct an absolute gravimetric quantification. The quantification of α-CPS by means of a calibration curve of cholesteryl sulfate can however be considered quite accurate since both molecules probably result in comparable detector responses of the ESI-MS for the following reasons: i) both α-CPS and cholesteryl sulfate carry a sulfate group and, without prior ionisation, are already negatively charged when reaching the ESI source. Different ionizabilities of both analytes can thus be excluded as source of inaccuracy. ii) The m/z ratios of α-CPS and cholesteryl sulfate are so close to each other (m/z=465.3039 vs. m/z=531.2992), that tuning of the mass spectrometer’s ion optics will not differently affect the detectability of either compound. iii) Just like the m/z ratios, the molecular masses of the molecules are comparable as well, so that differences with respect to spray formation in the ESI source are probably of minor importance. In conclusion it is reasonable to assume that quantification of α-CPS as equivalents of cholesteryl sulfate results in minor inaccuracies only.”

Also, reviewer 2 states: It is necessary to present the concentrations clearer. E.g., the size of the fish should be mention as the release of the kairomone might be correlated to fish size. How large where the fish for gall bladder extraction? How much bile has been extracted in Rainbow trout?

We acknowledge the point that size of fish might be related to release of the kairomone and have now included this information in Material and Methods “body size 10– 20 cm”. We do have information about the size of the fish used for gall bladder extraction (2 mL of bile from a trout of 1 kg weight). Please note, that not all bile extracted from a single fish but instead only aliquots of this were used. We therefore felt that neither information on body mass nor on extracted bile volume would make sense and have therefore not included this information. However, if the reviewers require it, we are of course willing to include the above give information on weight and total bile extracted from an individual fish.

The reviewers also discussed the validity of the term bioassay guided fractionation: The approach used is known as "bioassay-guided fractionation", by which compounds purified from fish exudates were tested for escape-inducing behavior, resulting in the eventual identification of a single molecule responsible for the observed effect on prey. The manuscript is largely focused on the process of identifying this molecule via a combination of chemical and behavioral experiments. The molecule, 5α -cyprinol sulfate, is a known product of the digestive systems of fish – a logical candidate for a cue that prey might use to sense their predators and respond defensively. Given the fact that the authors just published a paper on this compound and its NMR data makes us wonder if we are not rather dealing with a targeted study confirming the activity of a logical candidate. This would twist the whole presentation but maybe leave a better feeling after reading. The current manuscript represents one such study. The fact that the molecule the authors identified was previously known (albeit present and active at low nanomolar concentrations), makes the chemistry of the study a little less exciting, but the biological implications are still important.

We acknowledge this point of concern. Below we give a detailed chronology of our approach hoping to convince the reviewers that we have performed a full bioassay-guided approach; it has by no means been a targeted-approach! Briefly, earlier chromatography of the extracted fish incubation water (EFI;using water-MeOH only) resulted in not well-focused biological activity spreading across fractions “Pre”, “8” and “9” (Author response image 1), so that going for less steep gradients with even less focused activity was no option.

Author response image 1

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We therefore investigated mass-scans spanning these three fractions “Pre”, “8” and “9”, which yielded one common prominent ion with m/z = 531.2941, (see Author response image 2, 4, 6). Comparisons of these three mass scans to corresponding mass scans from a previous blank run confirm that two masses can be neglected since they are constitutively detected in the blank run and that of EFI: 1) m/z=68.9942 (highlighted in red) and 2) m/z=112.9836 (highlighted in green). Excluding these contaminants after blank subtraction resulted in m/z=531.2941 to be the most prominent detected ion in fractions “Pre” (Author response image 2) and “8” (Author response image 4) and the one with the third highest signal detected in fraction “9” (Author response image 6).

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Both pieces of information, the accurate mass and the presence of sulfate, yielded 5α-CPS as a candidate. Since 5α-CPS is not commercially available, we asked Dr. Hagey who kindly provided reference material, which actually was material that he had obtained from his predecessor, Dr. Haslewood, and which was without any information concerning its purity or even its structural elucidation. We received too little material for NMR of this putative reference compound. Although this material from Dr. Hagey showed identical HR-mass and retention time with our compound (see Figure 3B,C in the manuscript) we still wanted to be sure about its chemical identity. Therefore, we isolated new material form carp bile and confirmed its structure by NMR. At that time, we decided to publish this structural elucidation as a separate paper, since it was a confirmation of an already known structure. Then, when being sure, that m/z=531.2941 represents 5α-CPS, we screened for further bile salts in fractions “Pre”, “8” and “9” and discovered that additional bile salts were present.

From there on we optimized our chromatography for the analysis of bile compounds, then using a different solvent system. This new mobile phase allowed for much more focused biological activity and much better resolution of bile compounds than with water-MeOH as mobile phases. It is these results that we now present in the manuscript. We would like to emphasize that at all stages of the research (as well in the part depicted in the paper) all fractions were always subjected to bioassays and the major activity was always considered/investigated further. We strongly regard this as a bioassay-guided approach, and, in line with this, we claim to have identified the major DVM-inducing compound. At no stage this approach has been a targeted approach.

Reviewer 3 is quite critical in this point: The paper is solid and clear, but it lacks the kind of general appeal that expected for publication in eLife. In particular, the Introduction is quite basic, written in a way that is unlikely to draw in strangers to chemical ecology. The Discussion is similarly restricted to similar systems (fish and plankton). The description of the impacts of predation, chemical cues, and predator escape strategies would need broadening and enriching to be appropriate for this kind of general journal. The chemistry-oriented results are not particularly accessible to a general biology readership. As currently presented, the work is more appropriate for a more specialized journal like J. Chem. Ecol. or one committed to publishing works about freshwater ecology such as Limnology and Oceanography. The section of the Discussion related to movement of zooplankton (and thus effects on their own prey, phytoplankton) and resulting impacts on nutrient cycling would be of particular interest to a limnological and oceanographic audience. After a discussion among the reviewers the study was considered to be important and appealing to warrant further consideration of a revised version of the manuscript but the concerns of reviewer 3 should be kept in mind during revision and re-drafting of the Introduction and Discussion.

We appreciate this remark and have thoroughly incorporated the issues raised. However, we admit, that it is not entirely clear what is meant by ‘lacks the kind of general appeal that is expected for publication in eLife’. Lakes and ponds are the best available freshwater source on the Earth's surface. Lakes are valued as water sources and for fishing, water transport, recreation, and tourism and, due to their outstanding importance, issues of management of lakes and ponds are of pivotal importance. One tool for lake management is food chain manipulation, which aims at manipulating the interaction of Daphnia and fish. Our paper provides a fundamentally new understanding of the interaction of Daphnia and fish, which is key to the functioning and ecosystem services of lakes and ponds, and we therefore would like to emphasize that we regard our findings as highly appealing for more general journals as eLife. In response to concerns raised we have provided two new first paragraphs in the Introduction, in which we introduce the general importance of predation, the distinction of direct and indirect effects of predators and the importance of chemical signalling in predator-prey interactions. We hope that this will more appropriate to draw in general biologists into an issue of chemical communication. We have further condensed statements about the chemistry of known kairomones in aquatic chemical communication from formerly three different paragraphs to a single paragraph starting with “The DVM-inducing kairomone that we report here is to […]”. We have further removed all aspects of nutrient recycling from the Discussion in order to be more focused on the main contribution of this manuscript. And we have now included an introductory definition for kairomone: “Such chemical cues are termed kairomones, if they mediate a transfer of information among species that impart a benefit to the receiving organism while not being beneficial for the producer”.

Introduction section / Discussion paragraph two: The statement “virtually nothing is known about the chemical nature […]" might have been true 10 years ago, however there is substantial progress in the field and while only few compounds have been fully investigated (these should be cited) several studies address the compound classes, functional modes of action etc. involved. This part of the Introduction should be expanded. This is a common notion among the reviewers "The authors suggest that virtually no aquatic kairomone has been identified, ignoring the recent publication of the Chaoborus kairomone – another relevant kairomone for Daphnia with some similarities (Weiss et al., 2018)."

We acknowledge this point. First, we would like to add that Weiss et al., 2018 had already been mentioned in the letter to the editor, but unfortunately not been included in the manuscript. We apologize for this. In response to this issue we have now included the few chemically identified kairomones in aquatic plankton and briefly discuss their chemical features. We are now stating in the Introduction “[…] recently progress has been made by identification of infochemicals involved in predator-prey chemical communication (Selander et al., 2015 Weiss et al., 2018, Poulin et al., 2018)”

In the Discussion we are now referring to the few identified compounds in more detail (the papers of Selander et al., 2015, Weiss et al., 2018, Poulin et al., 2018 and Uchida et al., 2008) and discuss chemical similarities starting with “The other few cases in zooplankton, for which chemical cues have been identified […]”.

Results second paragraph: The calculation is incorrect. The value 532.29993 would suggest that H has a mass of 1. It is however 1.007 will lead to a calculated mass of 532.30693.

Yes, we agree. We changed the m/z from 532.29992 to 532.3070.

Results second paragraph: Why is a data base search required to determine the sum formula from a high res mass? The software of the instrument can simply calculate this.

Yes, indeed we calculated it using the tool sCLIPS included in the software MassWorks (cerno BIOSCIENCE). We mention the procedure in the Results: “The tool sCLIPS included in the software MassWorks (cerno BIOSCIENCE) was used to predict the corresponding sum formula of the detected molecule based on the detected peak of its monoisotopic mass as well as its isotope pattern. The predicted sum formula for [M-H]- was C27H48O8S. A data base search using the platform PubChem yielded as best hit cyprinol sulfate (CPS), a known bile compound of fish as a candidate compound for the DVM-inducing activity. This finding was well in accordance with the detected sulfate group.”

In the same paragraph: The step from the high res mass to the structure is not clear. Is the entire process only based on this one MS?

We agree. The structure was elucidated not only using the high res mass. Now, we present the procedure step by step in the Results (see the point above).

Figure 3: Are there explanations for the peaks at 2.04 and 2.38?

The identity of the ion detected at 2.04 min is unknown. The peak at 2.38 min is most probably derived from the isomer β-cyprinol sulfate, since Oncorrhynchos mykiss is known to synthesize β-bile alcohols (Hagey et al., 2010). There was no reference compound available to confirm its identity by retention times. We mention these peaks as follows:

“While the ion detected at 2.04 min is of unknown identity (Figure 3 D), we speculate that the second peak in the EIC of m/z=531.29986 at 2.38 min (Figure 3 E) is the isomoer β-cyprinol sulfate.”

Figure 4: The structures are the major result of the paper – they could be plotted bigger. The stereocenter on the C/D ring carbon of CPS should be indicated. Is there any information about the stereochemistry in the side chain?

Yes, we agree. We now also depict the missing protons, indicating the stereocenter on the C/D ring Carbon of CPS and enlarged the plots of all structures. (Figure 4) Unfortunately, there is no information available on the stereochemistry of the side chain.

Results paragraph five: The negative ionization ESI MS in Figure 4—figure supplement 1 can by no means be seen as a proof of purity. In fact, negative ionization only picks up a fraction of compounds in a mixture and in addition, the MS is not clearly indicating a pure compound. Show at least chromatograms in positive and negative ionization mode if no NMR data are available.

Yes, we agree. Following your request, we now replaced Figure 4—figure supplement 1 by chromatograms of the purified α-CPS in positive and negative ionization mode, as well as chromatograms of blank runs for comparison (Figure 4—figure supplement 1). Additionally, we inserted mass spectra spanning the chromatogram’s time window which is exhibiting peaks in the α-CPS but not in the blank runs to seek for impurities (Figure 4—figure supplement 2).

Discussion paragraph six and onwards: The discussion loses focus. Results from freshwater systems (this paper) are mixed with marine / oceanographic facts and become very speculative. The paper should focus more. Constructing e.g. a story about ocean acidification from the results is not justified.

Also: Salmon louse responses to CPS have to be proven, deduction from an uncharacterized receptor sequence to a DVM response are not warranted. Basically, a speculation is built on a speculation.

We agree and have removed both aspects from the Discussion.

Reviewer #2

Some studies are ignored that proved that UV-radiation is also inducing DVM in Daphnia, showing that it is additionally a strategy leading to avoidance of harmful irradiation (see. Rhode et al., 2001 or Leech and Williamson (2001, L and O).

Ringelberg and van Gool, 1998, suggest that bacteria are responsible at a certain step of the kairomone production as addition of an antibiotic prevented depth selection behavior. This might be addressed in the Discussion.

We are now addressing this aspect in the Discussion by stating:

“Neither this finding nor the fact that α-CPS, a fish metabolite that has not been microbially modified, constitutes the major kairomone in fish incubation water support the suggestion that bacteria are involved in the production of the kairomone (Ringelberg and van Gool, 1998).”

Specific comments:

I suggest changing the title to indicate that currently 5α-CPS has been shown to induce DVM in Daphnia magna and most likely in all daphnids. There is no indication that other genera respond to this kairomone.

"A bile salt from fish induces diel vertical migration in Daphnia"

Accordingly, we have changed the title into: “5α-cyprinol sulfate, a bile salt from fish, induces diel vertical migration in Daphnia”.

Author details

1. Meike Anika Hahn

   Aquatic Chemical Ecology, Department of Biology, University of Koeln, Koeln, Germany

   Contribution

   Data curation, Software, Investigation, Visualization, Methodology, Writing—original draft, Writing—review and editing

   For correspondence

   meike.hahn@uni-koeln.de

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-5090-0849

2. Christoph Effertz

   Aquatic Chemical Ecology, Department of Biology, University of Koeln, Koeln, Germany

   Contribution

   Investigation, Methodology

   Competing interests

   No competing interests declared

3. Laurent Bigler

   Department of Chemistry, University of Zurich, Zurich, Switzerland

   Contribution

   Resources, Methodology

   Competing interests

   No competing interests declared

4. Eric von Elert

   Aquatic Chemical Ecology, Department of Biology, University of Koeln, Koeln, Germany

   Contribution

   Conceptualization, Resources, Data curation, Supervision, Investigation, Methodology, Project administration, Writing—review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-7758-716X

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