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First published online May 21, 2007
Journal of Experimental Biology 210, 1992-1999 (2007)
Published by The Company of Biologists 2007
doi: 10.1242/jeb.02777
Phosphatidylcholine profile-mediated group recognition in catfish
1 Graduate School of Agricultural and Life Sciences, The University of
Tokyo, 1-1-1 Yayoi, Bunkyoku, Tokyo, 113-8657, Japan
2 Graduate School of Arts and Sciences, The University of Tokyo, 3-8-1
Komaba, Meguro-ku, Tokyo 153-8902, Japan
* Author for correspondence at present address: Monell Chemical Senses Center, 3500 Market Street, Philadelphia, PA 19104, USA (e-mail: kmatsumura{at}monell.org)
Accepted 15 March 2007
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Summary |
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Key words: chemical signal, recognition system, social organization
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). Recognition between members is often dependent on distinct
chemical signals that are emitted from them
(Wyatt, 2003). Although the
chemical signals governing sexual behaviors have been well characterized in
insects and in mammals, little is known about the chemical cues that provide
information about cognitive processes such as identifying the characteristics
of individuals (Dulac and Torello,
2003). Such signals must be the key to investigating the
mechanisms that govern not only perception and cognition, but also social
behaviors elicited by natural stimuli
(Dulac and Torello, 2003;
Schaal et al., 2003).
Therefore, identification of the salient cues is important for understanding a
wide variety of animal communications.
Recent advances in olfactory research have provided the opportunity to
identify unknown chemical signals involved in communications
(Brennan and Zufall, 2006). It
is well known that the individual status of conspecifics is discerned by a
complex mixture of chemicals, as reported in a wide range of animals from
invertebrates to vertebrates (Dulac and
Torello, 2003). In social insects, cuticular hydrocarbons can
convey information of individual status, by which their stable society is
organized (Steinmetz et al.,
2003; D'Ettorre and Heinze,
2005). Likewise, in higher vertebrates, complex mixtures of
metabolites are used for the identification of other individuals
(Dulac and Torello, 2003;
Brennan and Zufall, 2006). In
most cases, however, signal identity among chemical mixtures is poorly
understood.
The catfish Plotosus lineatus is a good model for studying group
(school) recognition via chemical signals
(Krause and Ruxton, 2002).
Soon after hatching, P. lineatus forms a school known as a clutch
(Kinoshita, 1975;
Matsumura, 2004;
Moriuchi and Dotsu, 1973;
Golani, 2002) (see Fig. S1 in
supplementary material), which appears as a highly cohesive ball-shape and has
a group organization based on familiarity. When two schools encounter each
other, they either merge into one school, or reform the separated schools,
depending on the situation (Kinoshita,
1975; Matsumura,
2004). Similar dynamic group organization has been reported in
many animals whose group members recognize each other through various sensory
systems, such as vision, audition, somatosensation and olfaction
(Kerth and König, 1999;
Barber and Ruxton, 2000;
Krause and Ruxton, 2002;
Parrish et al., 2002;
Camazine et al., 2003).
Schooling in P. lineatus is also organized by the visual,
lateral-line and chemical senses (Sato,
1938; Kinoshita,
1975; Hayashi et al.,
1994). Discrimination between familiar and unfamiliar schools in
P. lineatus is governed by a chemical signal originating from school
members, enabling them to discriminate between odors of familiar and
unfamiliar schools (Kinoshita,
1975; Hayashi et al.,
1994). In addition, chemical signals for school recognition are
perceived through olfaction because naris-occluded individuals were not
attracted to seawater in which the familiar school had been maintained
(Hayashi et al., 1994).
However, the chemical signal underlying school recognition is yet to be
elucidated. Previously, we established a behavioral bioassay to estimate the
recognition of school odor in individual fish
(Matsumura et al., 2004).
Using the bioassay, we deduced that school odor is a mixture of
phosphatidylcholine (PC) molecular species; however, its precise functions
remained unsolved (Matsumura et al.,
2004). Therefore, the present study asks: (1) are PCs alone
sufficient to elicit and be solely responsible for recognition of school odor?
(2) Does P. lineatus discriminate between familiar and unfamiliar
PCs? (3) Are PC profiles indispensable to expression of recognition activity
of school odor?
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Materials and methods |
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Extraction and isolation of PC
Preparation of PC from P. lineatus was essentially as described
previously (Matsumura et al.,
2004). Ethanol extract of skin mucus collected from school members
was partitioned between water and chloroform, and the chloroform layer was
loaded onto a polystyrene column (TSK G3000S, Tosoh, Tokyo, Japan; 70
mmx10 mm i.d.) and eluted with 50 ml each of 70%, 90%, 100% methanol,
followed by chloroform/methanol (1:1). The fractions eluted with the last
three solvents were combined and separated by HPLC on a polyamide column (250
mmx20 mm, YMC Pack Polyamide II, Yamamura Chemical Laboratories, Kyoto,
Japan) at a flow rate of 3.5 ml min–1 with
acetonitrile/methanol/water (73:25:3 v/v) to yield a PC fraction. This
material was further separated by HPLC on an ODS column (Phenomenex Luna 5
µ, 250x10 mm, Phenomenex, Torrance, CA, USA) at 3 ml
min–1 with 100% methanol into Fraction 1 and Fraction 2.
Bioassay
Procedures for bioassay and data analysis were essentially the same as
described previously (Matsumura et al.,
2004). In brief, a test fish, chosen at random from a test school,
was introduced into a test device (68 cmx40 cmx15 cm; seawater, 3
cm depth) and acclimated for 3 min (i.e. to constant swimming behavior). Agar
blocks (1 cm3) containing a test solution and the solvent
(methanol) were attached to each side of the container using a metal wire (2
cm longx0.1 cm diameter). P. lineatus presented a
characteristic behavior towards the agar blocks that contained the school odor
(i.e. the fish returned to the agar blocks after first passing them). The
response of the test fish to the agar blocks was video recorded for 5 min. The
positions of the treatment and control agar blocks were switched during
successive trials. Test individuals, test seawater and stimulants were
replaced at each trial. The number of trials is given in Table S1 in
supplementary material. All samples were assayed blind. All behavioral assays
were carried out at a PC concentration of 0.15 mg ml–1,
except for the dose–response experiment shown in
Fig. 1. To assess the ability
of P. lineatus to distinguish between PCs obtained from two schools
(school A and school B), the following combinations of samples were used:
school A vs control (methanol), school B vs control, school
A vs school B, and control vs control. In order to modify
the PC profile, PC was supplemented with 0.1, 1 and 10% (w/w) of either
1-palmitoyl-2-(4,7,10,13,16,19-(E)-docosahexaenoyl)-sn-glycero-3-phosphocholine
[16:0-22:6 (SPC1)] or
1-hexadecanoyl-2-(5,8,11,14-(E)-eicosatetraenoyl)-sn-glycero-3
phosphocholine[16:0-20:4 (SPC2)] (Sigma, St Louis, MO, USA).
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). In
brief, the number of passes to the agar blocks (N) and turns to the
agar blocks (n) were counted; a turn was counted only when the test
fish returned to the agar block within 5 s of passing it. The percentage of
turns (RT) was calculated using the following equation:
RT=(n/N)x100. RT was transformed to arcsine values
using the following equation: transformed value (TV, degree)=arcsine
(RT/100)1/2 (see supplementary material Table S1 for the statistical analysis
between TVs) (Zar, 1999). To
compare the activity between each stimulus, a response index (RI) was
calculated using the following equation:
RI=[(RTT–RTC)/(RTT+RTC)]x100, where RTT is the RT obtained for the
treatment agar block and RTC is that for the control agar block. RI of each
sample was compared using a two-sample t-test. The statistical
analysis was performed using the computing software R
(http://www.r-project.org).
In all figures, values are means ± standard error of the mean
(s.e.m.).
Analysis of PC molecular species
A diethyl ether/ethanol (95:5, v/v) solution of PC (1 mg in 500 µl) was
added to 100 µl of buffer (100 mmol l–1 Tris-HCl, 20 mmol
l–1 CaCl2, pH 7.3) containing 0.5 mg of
Clostridium perfringens phospholipase C Type XIV (PLC; Sigma), and
the mixture was incubated at 37°C for 2 h. The solution was extracted with
diethyl ether (3x300 µl), and the ether extracts were dried in
vacuo to obtain 1,2-diacyl glycerol (1,2-DG). 1,2-DG was dissolved in 500
µl dry toluene (Wako Pure Chem, Osaka, Japan) and 30 µl dry pyridine
(Wako Pure Chem), and 3,5-dinitrophenyl isocyanate (3 mg; Aldrich, St Louis,
MO, USA) was added to this solution. The mixture was allowed to stand for 1 h
at room temperature. To quench the reaction, methanol (100 µl) was added to
the reaction mixture; the solvents were removed in a stream of nitrogen gas.
The residue was purified using TLC (Silica Gel 60 F254, 8x20 cm, 0.25 mm
thick; Merck, Whitehouse Station, NJ, USA). The TLC plate was developed with a
mixture of n-hexane/dichloromethane/ethanol (40:10:3, v/v/v). A band
corresponding to the 1,2-DG derivatives (Rf, 0.58) was
scraped off and extracted with diethyl ether. The ether extract was dried
in vacuo to furnish the dinitrophenylurethane (DNPU) derivatives of
1,2-DG (Okabe et al.,
1999).
The PC DNPU derivatives [10 µl (1 mg ml–1 methanol)] were analyzed by an HPLC system consisting of a Waters 2695 Separations Module and Waters 2996 photodiode array (PDA) detector (Waters Corporation, Milford, MA, USA). The following five columns were connected for the isolation of PC components: Prodigy ODS-3 (Phenomenex), Luna 5 µ C18(2) (Phenomenex), TSKgel ODS-80Ts (Tosoh), two Inertsil ODS-3 (250x4.6 mm each; GL Sciences, Tokyo, Japan). The column temperature was maintained at 23°C; the column was eluted with acetonitrile/isopropanol (8:2) at a flow rate of 0.5 ml min–1, and peaks were detected by UV absorption at 254 nm. The recordings of chromatogram and the quantitative analysis of peak areas were analyzed using Waters Empower PDA software (Waters Corporation, Milford, MA, USA; see Fig. 2). Fatty acids in PC were identified by a combination of mass spectrometric (JMS-700T; JEOL, Tokyo, Japan) and gas chromatographic (GC) analysis. In brief, fast atom bombardment (FAB) mass spectra of the isolated PC DNPU derivatives were recorded using m-nitrobenzyl alcohol as a matrix (Fig. 4A). The PC DNPU derivative, isolated by HPLC, was dissolved in 1 ml of 0.5 mol l–1 sodium methoxide. The solution was kept at 50°C for 10 min. After cooling to room temperature, the reaction mixture was partitioned by adding 0.1 ml of acetic acid and 4 ml each of water and n-hexane. Subsequently, the aqueous layer was extracted twice with n-hexane. The extracts were dried in a stream of nitrogen gas, dissolved in n-hexane, and analyzed by GC using a Shimadzu GC-9A gas chromatograph on SPTM-2380 column (30 mx0.25 mm i.d.; Supelco, St Louis, MO, USA). Helium was used as a carrier gas and temperature was maintained at 140°C for 5 min followed by programmed increases of 3°C min–1 up to 240°C (Fig. 4B). The structures were determined by comparing the retention time of standard fatty acid methyl esters.
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),
Zij=ln[Yij/g(Yj)],
where Zij is the standardized peak area i for school j,
Yij is the peak area i (No. 1–19) for school j (47
schools), and g(Yj) is the geometric mean of peaks for
school j. The transformed areas were used as variables in a PCA operated by a
custom program with R
(http://www.r-project.org)
to obtain the principal component scores and proportions. A two-dimensional
(2D) space was spanned by the two leading principal components (PC1 and PC2;
Fig. 5E). The schools (47
schools in total) were again sorted on the basis of the first principal
component (PC1) to represent a square correlation matrix
(Fig. 5F). The figure is
symmetrical about the diagonal of those in which the darker black colors
represent lower correlations and the lighter colors, higher correlations.
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TOPSummaryIntroductionMaterials and methodsResultsDiscussionReferences |
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),
which suggested that school odor is a mixture of PC molecular species, we
first compared the turn behavior-eliciting activity of the skin mucus and the
PC isolated from the skin mucus. The dose–response curves for skin mucus
and PC, ranging from 0.0015 to 0.3 mg ml–1, were not
significantly different [two-way ANOVA: P<0.05
(N=7–12; d.f.=4, F4,94=3.305,
P=0.0146 for doses; d.f.=1, F1,8=0.0144,
P=0.905 for skin mucus vs PC in
Fig. 1; for the number of
turns, see Table S1 in supplementary material)]. Thus, PC elicits the typical
turn behavior in P. lineatus as efficiently as the skin mucus. In
contrast, egg yolk- and soybean-derived PCs did not elicit turn behavior in
P. lineatus (K.M., S.M. and N.F., unpublished results), suggesting
that PC originating from the skin mucus is essential for recognizing school
odor.
Discrimination between familiar PC and unfamiliar PC
P. lineatus was reported to discriminate between the odors of
familiar and unfamiliar schools
(Kinoshita, 1975). Therefore,
we examined whether P. lineatus can recognize familiar PC using the
two-choice test (School A vs School B). The results showed that a
school member clearly selected the skin mucus of the familiar school rather
than the control or the skin mucus of the unfamiliar schools
(N=8–13; two sample t-test, P<0.05;
Fig. 2A,B; for the number of
turns, see Table S1 in supplementary material), indicating that P.
lineatus distinguishes between familiar and unfamiliar mucus. This is
also true for PCs; the school members selected the PC of the familiar mucus
but not that of the control or the unfamiliar PCs (N=9–15; two
sample t-test, P<0.05;
Fig. 2C,D; for the number of
turns, see Table S1 in supplementary material). These results indicate that
P. lineatus discriminates between the odors of familiar and
unfamiliar schools by their PC content.
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Heterogeneity of PC profile
Using quantitative HPLC analysis of PC molecular species, as shown in
Fig. 4, we examined HPLC
profiles of PCs prepared from 47 schools. The results clearly showed that
schools contained a similar set of PC molecular species, but their relative
proportions varied from school to school (see selected example shown in
Fig. 5A–D), indicating
that each school has a specific PC profile. To confirm the diversity of PC
profiles between schools, we conducted principal component analysis (PCA) of
47 schools.
The multidimensional PCA data were projected onto a two-dimensional space spanned by the two leading principal components (Fig. 5E); selected profiles of Fig. 5A–D (boxed) are plotted in scattered positions onto a two-dimensional space. PCA revealed distinct variations in the PC profiles without a specific distribution pattern among the schools. In other words, each school had a school-specific PC profile. Moreover, the overall visual representation of the similarities between PC profiles among schools was carried out after sorting the schools based on PC1, in which the school-by-school correlation matrix was graded by tones varying from black to white (Fig. 5F). The correlation matrix clearly showed PC1-based graded similarities among the PC profiles of the schools whose correlation coefficients range from 0.656 to 1 (1 meaning auto correlation). For example, the correlation coefficient between the profiles of Fig. 5A,D is 0.875 (A vs D=0.875). Thus, the PC profile, comprising remarkably diverse molecular species, is the signature of each school, suggesting its involvement in school recognition.
Responsibility of PC profile
To address whether P. lineatus recognizes a single PC molecular
species or PC profiles, we divided the PC molecular species into two fractions
using HPLC (Fig. 6A) and
evaluated the turn behavior caused by each fraction
(Fig. 6B). Neither fraction
(Fr.) 1 nor Fr. 2 elicited turn behavior, while the re-constructed PC (mix)
was as active as the original PC (approximately 90% identical,
N=9–11; P<0.05;
Fig. 6B; for the number of
turns, see Table S1 in supplementary material). This result indicated that at
least two PC molecular species are involved in school recognition. In other
words, the result suggests that school-specific recognition is responsible for
the profile of more than two PC molecular species. We then modified the PC
profile by adding two synthetic PCs, SPC1 [16:0-22:6(n-3)] and SPC2
[16:0-20:4(n-6)], which are known to be present in skin mucus of P.
lineatus. Addition of 10% (w/w) of either SPC1 or SPC2 significantly
diminished the activity of the original PC (P<0.05), while
approximately 50% of the original activity was lost by adding 1% SPC1 or SPC2
(Fig. 6C; for the number of
turns, see Table S1 in supplementary material). The addition of 0.1% SPCs did
not affect the activity (P<0.05;
Fig. 6C). Incidentally, neither
SPC1 nor SPC2 individually showed the activity
(Fig. 6C). These results
indicate that the profiles of PC molecular species are responsible for the
activity. Thus, we concluded that PC profile encodes school recognition in
P. lineatus.
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) suggested that the composition of PC molecular species is
different from school to school, allowing P. lineatus to discriminate
their own school from others. To support this hypothesis, we attempted in this
study to demonstrate that recognition of school odor in P. lineatus
is determined by a school-specific PC profile constructed from its diverse
molecular species. First, we showed that P. lineatus can clearly
discriminate between the odors of a familiar school and unfamiliar ones using
PC, indicating that PC is a reliable signal for the recognition of a familiar
school. To reveal school-specific PC profiles, PC molecular species were
analyzed by a combination of HPLC and mass spectrometry. Each school contained
the same set of PC molecular species, but not the same specific PC molecular
species (Fig. 5A–D). In
addition, the mixing pattern of the PC molecular species (PC profile) was
highly heterogeneous between schools, as determined by PCA and correlation
matrix (Fig. 5E,F). Thus, these
results suggest that the cue for the recognition of the school odor is the
mixing pattern of the PC molecular species that are blended for each school,
but not any limited molecular species that is specialized for each school. In
fact, modification of the PC profile, by addition of synthetic PCs, resulted
in loss of the activity (Fig.
6). Thus, the complete PC profile is necessary for recognition of
the school odor that underlies the organization of the P. lineatus
school.
Use of chemical blends might increase the specificity of recognition and
allow the transmission of more complex messages because the use of mixtures is
well documented in many species and situations
(Dulac and Torello, 2003). In
ants, pheromones, often released as chemical blends, show extreme specificity
in identifying the social status of the ants. Alarm pheromones are mostly
composed of two or more chemicals that are used simultaneously to alert,
attract and evoke aggression (Ono et al.,
2003). In goldfish (a vertebrate), steroid hormone products have
been identified as pre-ovulatory sex pheromones. Interestingly, three
different pheromone blends can elicit varying degrees of male courtship or
aggressive behavior in recipients (Poling
et al., 2001). Group organization also requires specificity of
recognition between group members in order to take advantage of many adaptive
functions such as anti-predation, energy consumption, food location,
cooperative reproduction (Bradbury and
Vehrencamp, 1998).
Chemical signals involved in the recognition of group members are,
therefore, often constructed from the mixture of the same repertoire of
chemicals. For instance, to recognize individuals social insects use a profile
of cuticular hydrocarbons, whose constituents are different from nest to nest
(Lahav et al., 1999;
Ozaki et al., 2005;
D'Ettorre and Heinze, 2005).
Likewise, vertebrates also use chemical profiles as communication signals to
discern the individual status of conspecifics such as parent–progeny,
mating partner and familiarity (Kerth and
König, 1999; Safi and
Kerth, 2003; Bloss et al.,
2002; Heymann,
2006). In the common marmoset, each female was found to have a
unique ratio of highly volatile chemicals in the scent mark that could affect
individual discrimination, which may play a key role in regulating both female
intrasexual competition and intersexual communication as well as in providing
a basis for the assessment of individual quality
(Smith et al., 2001;
Smith, 2006). These reports,
however, only proposed candidates for chemicals underlying group identity and
did not identify the chemicals. Our report is thus the first identification of
a chemical signal underlying recognition of group odor in vertebrates. The
mode of recognition of school odor mediated by the PC profile in P.
lineatus resembles a chemical signature, enabling recognition of the
group, as described in other animals. The present work thus provides an
important example of chemical profile-based recognition as a common scheme for
group integration. The remaining issue is to identify which PC molecular
species are essential for the expression of activity.
Influence of chemical profile
Communication via a chemical signal, as described above, is
influenced by both genetic factors and environmental conditions. As a genetic
factor, it is well known that the major histocompatibility complex
(MHC)-related metabolites are involved in a variety of individual choice
processes (Milinski et al.,
2005; Willse et al.,
2005; Boehm and Zufall,
2006). Although the mechanism for odor production influenced by
MHC loci is not entirely clear, some rodents and humans are able to
distinguish individuals who vary in this gene complex. In addition, mouse
urinary proteins, members of the lipocalin family, are responsible for the
binding and release of volatile chemicals, a contributing role in the
communication of individual identity
(Hurst et al., 2001). A
similar mechanism might be involved in the case of P. lineatus if
recognition of school members occurs among individuals that share similar MHC
regions. Genetic similarity between school members could be explained from the
beginning of P. lineatus schooling. During the spawning season, a
spawning pair of P. lineatus digs a nest on a sandy bottom under
rocks in shallow water where hundreds of eggs are laid. After the egg clutch
has hatched, the juveniles stay on the bottom and start schooling within a
week (Moriuchi and Dotsu,
1973). Therefore, school members must have a similar genetic
composition as well as similar MHC loci. However, genetic similarity of school
members becomes more unpredictable as they grow, because fully grown schools
will have already been mixed repeatedly with other schools. Accordingly, the
degree of genetic relatedness among school members must be a key to
understanding school organization in P. lineatus.
In addition to genetic factors, environmental factors also influence the
composition of signal substances, with diet being particularly important. In
fact, diet manipulation changes body odors that are involved in individual
recognition and social relationships in various animals
(Bryant and Atema, 1987;
Liang and Silverman, 2000;
Olsén et al., 2003).
This implies that diet is a significant factor in the production of a
distinctive body odor. Similarly, the diet condition of a P. lineatus
school might contribute to the diverse heterogeneity of PC profiles between
schools, as shown in Fig.
5A–E. Therefore, in addition to the examination of genetic
similarity, PC molecular species collected from schools at every growth stage
must be analyzed. In other words, the results obtained could provide a
possible mechanism for integrating school organization of P. lineatus
from the aspects of both genetic factors and environmental conditions.
Perception of chemical mixture
Odor mixtures and their patterns can elicit characteristic responses at
every stage of sensory processing: olfactory receptor
(Oka et al., 2004), olfactory
bulb (Tabor et al., 2004),
olfactory cortex (Zou and Buck,
2006), and behavioral expression
(Valentincic et al., 2000;
Uchida and Mainen, 2003).
Recently, the neural response to natural odors such as seasoning, food and
animal odors was elegantly recorded from the dorsal surface of the main
olfactory bulb, indicating that odor mixtures are encoded by sparse
representation in the olfactory bulb (Lin
et al., 2006). These learning and processing mechanisms for
complex odor mixtures can help us to understand the perception mechanism of PC
molecular species in P. lineatus. For example, P. lineatus
starts schooling soon after hatching from an egg clutch
(Moriuchi and Dotsu, 1973),
suggesting that the familiar school-specific odor (PC profile) is imprinted
during the early developmental stage. In addition, P. lineatus
forgets the familiar school odor within a day, and a lost individual can learn
an unfamiliar school odor (Kinoshita,
1975). The results indicate that school recognition in P.
lineatus is plastically controlled after growth. Therefore, the learning
mechanism of school-specific odor (mixing pattern of PC molecular species)
could be an important example in which to investigate the rewiring and
maintenance of neural substrates underlying the memory of complex chemical
mixtures.
Our study of the complex chemical mixture underlying the recognition of group odor by P. lineatus provides valuable insights into recognition mechanisms mediated by chemical signals. Furthermore, understanding how such a complex signal is represented will not only provide insight into neural strategies for coding of social signals, but also suggest a paradigm for understanding more generally how natural olfactory scents are represented in the olfactory bulb, and beyond that, how social behavior is conducted.
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Acknowledgments |
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Footnotes |
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Present address: Graduate School for Fisheries Sciences, Hokkaido
University, 3-1-1 Minato-cho, Hakodate 041-8611, Japan 
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