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Chapter: 4 Pheromone-mediated gene expression in the honey bee brain

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Suggested Citation:"4 Pheromone-mediated gene expression in the honey bee brain." National Academy of Sciences. 2003. Chemical Communication in a Post-Genomic World. Washington, DC: The National Academies Press. doi: 10.17226/10965.
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Suggested Citation:"4 Pheromone-mediated gene expression in the honey bee brain." National Academy of Sciences. 2003. Chemical Communication in a Post-Genomic World. Washington, DC: The National Academies Press. doi: 10.17226/10965.
×
Page 8
Suggested Citation:"4 Pheromone-mediated gene expression in the honey bee brain." National Academy of Sciences. 2003. Chemical Communication in a Post-Genomic World. Washington, DC: The National Academies Press. doi: 10.17226/10965.
×
Page 9
Suggested Citation:"4 Pheromone-mediated gene expression in the honey bee brain." National Academy of Sciences. 2003. Chemical Communication in a Post-Genomic World. Washington, DC: The National Academies Press. doi: 10.17226/10965.
×
Page 10
Suggested Citation:"4 Pheromone-mediated gene expression in the honey bee brain." National Academy of Sciences. 2003. Chemical Communication in a Post-Genomic World. Washington, DC: The National Academies Press. doi: 10.17226/10965.
×
Page 11
Suggested Citation:"4 Pheromone-mediated gene expression in the honey bee brain." National Academy of Sciences. 2003. Chemical Communication in a Post-Genomic World. Washington, DC: The National Academies Press. doi: 10.17226/10965.
×
Page 12
Suggested Citation:"4 Pheromone-mediated gene expression in the honey bee brain." National Academy of Sciences. 2003. Chemical Communication in a Post-Genomic World. Washington, DC: The National Academies Press. doi: 10.17226/10965.
×
Page 13

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Colloquium Pheromone-mecliatecl gene expression in the honey bee brain Christina M. Grozinger*~§, Noura M. Sharabasht, Charles W. Whitfieldtt, and Gene E. Robinsont: *Beckman Institute for Advanced Science and Technology, "Department of Entomology, and "Neuroscience Program, University of Illinois at tJrbana-Champaign, Urbana, IL 61801 We tested the hypothesis that queen mandibular pheromone (QMP) causes changes in gene expression in the brain of the adult worker honey bee, and that these changes can be correlated to the downstream behavioral responses induced by QMP. In support of the first hypothesis, cage experiments revealed that QMP tran- siently regulated expression of several hundred genes and chron- ically regulated the expression of 19 genes. Several of these genes were also affected by QMP in experiments with bee colonies in the field, demonstrating robust gene regulation by pheromone. To evaluate the second hypothesis, we focused on one function of QMP: delaying the transition from working in the hive (e.g., brood care, or "nursing") to foraging. We compared the list of QMP- regulated genes with the lists of genes differentially regulated in nurse and forager brains generated in a separate study. QMP consistently activated "nursing genes" and repressed "foraging genes," suggesting that QMP may delay behavioral maturation by regulating genes in the brain that produce these behavioral states. We also report here on an ortholog of the Drosophila transcription factor kruppel homolog 1 that was strongly regulated by QMP, especially in the mushroom bodies of the bee brain. These results demonstrate chronic gene regulation by a primer pheromone and illustrate the potential of genomics to trace the actions of a pheromone from perception to action, and thereby provide in- sights into how pheromones regulate social life. Many animal species, from insects to mammals, communi- cate via pheromones, chemicals that cause dramatic al- terations in physiology and behavior. The recent identification of olfactory and pheromone receptors in Drosophila melanogaster and the mouse have provided new insights into how the olfactory system senses and encodes odorants (reviewed in refs. 1 and 2~. It also has been demonstrated that pheromones affect gene expression in brain neurons, particularly with respect to imme- diate-early genes (3, 4~. However, the molecular mechanisms by which pheromones are further transduced in the brain to influ- ence behavior are only beginning to be understood (14. Partic- ularly interesting are long-term changes in brain gene expression that might result from exposure to primer pheromones. These long-term changes in gene expression may be responsible for inducing long-term changes in physiology and behavior, a hall- mark of primer pheromone action. Here we report on our efforts to use the honey bee (Apis mellifera) to study the effects of a primer pheromone on brain gene expression. We also have begun to correlate these gene expression changes with phero- mone-mediated behavioral changes. Honey bees show complex social organization that is con- trolled to a large extent by pheromones, many of which have been well characterized, both chemically and with respect to their specific behavioral effects (5-8~. We studied the best understood bee pheromone, queen mandibular pheromone (QMP), a well- characterized blend that is part of a recently identified nine- component pheromone that attracts workers to attend the queen (9~. QMP consists of five chemicals: (E)-9-keto-2-decenoic acid www.pnas.org/cg i/doi/ 10.1 073/pnas.2335884100 (9-ODA), (R,E)-~-~- and (S,E)-~-9-hydroxy-2-decenoic acid (9HDA), methyl p-hydroxybenzoate (HOB), and 4-hydroxy-3- methyoxyphenylethanol (HVA) (7~. QMP plays many roles in social regulation (7~. It prevents reproduction both by inhibiting worker ovary development (10) and the rearing of new queens (11~. It may control brain development in the olfactory system of young bees (12~. QMP also influences age-related division of labor among worker bees. Bees perform in-hive tasks such as brood care (nursing) for the first 2-3 weeks of their adult life and switch to foraging for food outside the hive in the last weeks of their life. Honey bees show many changes in physiology in association with this behavioral maturation, including structural changes in the mushroom bodies of the brain (which are sites of multimodal sensory integration and higher-order functions such as learning and memory), and differences in brain gene expres- sion in nurses compared with foragers (13, 14~. QMP delays honey bee behavioral maturation (15~. In this article we report on experiments that test two hypoth- eses: exposure to QMP causes changes in gene expression in the brain, and these changes correlate with the downstream behav- ioral effects of the pheromone. We used a recently developed honey bee brain microarray (16) to profile pheromone-induced changes in brain gene expression. Experiments were performed both with cage studies under controlled conditions in the labo- ratory and natural colony conditions in the field, to determine the robustness of the QMP effects. Because differences in gene expression associated with nursing and foraging behaviors have been analyzed extensively with microarrays (14), we used this information to explore our second hypothesis, that pheromone- regulated changes in gene expression are correlated with pher- omone-induced changes in behavior. Finally, we began to char- acterize the effects of QMP on an ortholog of the Drosophila transcription factor kruppel homolog 1 (~Kr-hl ~ (17), a particularly promising candidate gene that emerged from our microarray analyses. ~ 1 Materials and Methods Genetic Manipulation. Worker bees were derived from queens that were instrumentally inseminated with semen from a single, different drone, according to established procedures (18~. Be- cause male bees are haploid, the coefficient of relatedness This paper results from the Arthur M. Sackler Colloquium of the National Academy of Sciences, "Chemical Communication in a Post-Genomic Woricl," held January 17-19, 2003, at the Arnold and Mabel Beckman Center of the National Academies of Science and Engineering in Irvine, CA. Abbreviations: QMP, queen mandibular pheromone; Kr-h1, kruppe/homo/og 1; qRT-PCR, quantitative RT-PCR. Data cieposition: Gene expression data meet Minimum Information About a Microarray Experiment (MIAME) stanclarcis and have been deposited at ArrayExpress (www.ebi.ac.uk/ arrayexpress). ITo whom correspondence shoulci be acidressecl. E-mail: grozinge~staff.uiuc.edu. 2003 by The National Acaclemy of Sciences of the USA PNAS 1 November 25, 2003 1 vol. 100 1 suppl. 2 1 14519-14525

among offspring of such an instrumentally inseminated queen is 0.75. Bees were obtained from three "source colonies," each headed by one of these queens, R8, R11, or R16. Bees from "genotype" R8 were used for the mieroarray experiments, and bees from R11 and R16 were used to confirm some of the mieroarray results with real-time quantitative RT-PCR (qRT- PCR), as described below. Rearing. Colonies were maintained at the University of Illinois Bee Research Facility according to standard commercial pro- cedures. To provide bees of known age, honeycombs containing late-stage pupae were removed from source colonies and placed in an incubator to emerge (33°C, 95% relative humidity). For cage studies, bees were collected 16 h after eelosion and placed in small (10 x 10 x 7 em) Plexiglas cages (35 bees per cage) for 8 h before pheromone exposure began. Bees were provided with water and food (45% honey, 45% pollen, 10% water). Cages were kept in a humidity-eontrolled (50% relative humidity), dark incubator at 33°C. Pheromone exposure eon- sisted of 0.1 queen equivalent (the typical amount found in one queen) of QMP (QMP+) or a solvent control (QMP-) intro- dueed on a glass slide. This dose is sufficient for inhibiting ovary development in caged worker bees (104. The duration of pher- omone exposure was 1, 2, 3, or 4 days. For each replicate, one entire QMP+ and one QMP- cage were flash-frozen in liquid nitrogen to prevent any additional changes in gene expression (19~. Heads were removed and stored at—80°C until dissection. Bees were sampled at the same time of day to minimize any variation caused by circadian rhythms. For field studies, the source colony was split into three colonies, allocating roughly equal quantities of adult bees, brood, and pollen and nectar stores. One colony retained the original queen (OR), one was left queenless (QL), and the third was given a strip that contained 10 queen equivalents (QMP+), a dose shown to mimic a live queen (20~. The three colonies were transferred to a different apiary >2 miles away so they would not return to the site of their natal hive. Before the colony split, bees (n ~1,500) were collected 0-36 h after eclosion, marked on the dorsal thorax with a paint dot (Testor's Paint, Roekford, IL), and ~500 were placed in each of the three colonies. Two days later, the marked bees were collected (n = 100~. Bees were collected into liquid nitrogen, and heads were stored as above. For gene expression analysis in the mushroom bodies, foragers were collected from two colonies (R5, R11) upon return from foraging flights, and 1-day-old bees were collected <24 h after eelosion. Pheromones. QMP was obtained from PheroTeeh (Delta, Can- ada). For cage experiments, 0.1 QMP was applied to glass slides in 10 Al of 1% H2O/isopropy1 alcohol and allowed to dry (9~. QMP was applied to a fresh slide at the same time every day. For field experiments, commercially formulated QMP strips (Phero- Teeh) were used and replaced daily (20~. Confirmation of Pheromonal Activity. To confirm QMP activity in cages, the effect of QMP on ovary development was assessed (10~. Cages of bees were set up as described above and main- tained for 10 days, then collected and stored at -20°C until dissection. The degree of ovary development was assessed according to Veltuis (214. Two cages from each of the three genotypes were analyzed. A total of 12 of 30 QMP- bees developed ovaries (with developed eggs and follicle cells), whereas 0 of the 30 QMP+ bees developed ovaries (P ~ 0.01, x2 test), demonstrating that the QMP was active and the bees were sensitive to it. To confirm QMP activity in the field, the effect of QMP on the number of queen cells built was determined. Queen cells are distinctive large cells on the honeycomb built by worker bees to 14520 1 www.pnas.org/cgi/doi/10.1073/pnas.2335884100 rear new queens (8~; QMP partially inhibits this behavior (11~. The number of queen cells built in QL colonies was 31, 29, and 12 (R8, R16, and R11, respectively) compared with 1, 5, and 5 queen cells built in the QMP+ colonies. In OR colonies, no queen cells were built in R8 and R16, whereas three were built in R11. QMP clearly suppressed queen eell-building behavior in the field. Brain Dissection. Whole bee heads were partially lyophilized to facilitate brain dissection (22~. Dissections were performed over dry ice so tissue never thawed. Because ocelli and the sube- sophageal ganglion frequently fractured during dissection, these were removed during all dissections, while the remainder of the brain was included. Mushroom bodies were dissected from freeze-dried brains as in ref. 22. Microarrays and Data Analysis. The mieroarray contained ~9,000 cDNAs, representing ~7,600 different genes, 40% of which have been annotated primarily by using comparisons to Drosophila genes and the molecular function classification scheme of the Gene Ontology Consortium (16~. This number is estimated to account for 50% of the genes in the honey bee genome, based on comparisons with the Drosophila genome. For cage studies, direct competitive hybridization compari- sons were made for matched samples of QMP+ and QMP- bees. Each sample consisted of 10 brains pooled (10 bees taken randomly from a cage of 35 bees after the entire cage was killed). Eight arrays were analyzed for each time point (1, 2, 3, or 4 days of pheromone exposure), a total of 32 mieroarrays. The eight replicates were comprised of four biological replicates (different cages) and four technical replicates. For field studies, each sample consisted of 10 brains pooled. Samples from the OR, QMP+, and QL colonies split from the R8 source colony were compared with each other in a loop design that used three microarrays, with four technical replicates, for a total of 12 arrays (23~. Dissected bee brains were homogenized in Trizol (Invitrogen Life Technologies), and RNA was extracted according to the manufacturer's protocols. mRNA was then purified by using an Oligotex mRNA kit (Qiagen, Valeneia, CA). eDNA synthesis and hybridization to mieroarrays followed protocols modified from ref. 24 and described in ref. 14. Arrays were scanned with GENEPIX software and normalized to the median intensity with regional and intensity-dependent Lowess normalization. Dyes used to label the QMP+ and QMP- samples were reversed in half of the replicates to control for dye-by-gene interactions. The following filtering protocols were followed, as in Whitfield et al. (144. eDNAs with average expression intensities across each set of eight arrays <350 or absent from > 1 array were removed from the analysis. eDNAs expressed at equal levels in hypopharyngeal glands in the honey bee head (14) were removed because material from these glands can sometimes contaminate dissected brains. Only eDNAs expressed at all time points and also in the Whitfield et al. (14) nurse vs. forager analysis were analyzed, to facilitate comparisons across the two studies. This left 6,360 eDNAs, representing ~5,000 unique genes. Bayesian analysis (25) was used to determine which eDNAs were significantly regulated by QMP. This method generates an estimated mean and 95% confidence interval (CI) for the relative level of expression of each eDNA for each experimental group of bees. eDNAs were classified as differentially expressed if their 95% CIs did not overlap between groups (one-tailed t test). This approach enables identification of small, but repro- dueible, differences in gene expression (26, 27~. Notably, the expression of most significantly regulated genes changed by ~10%. For example, of 2,607 eDNAs found to be significantly regulated during the time course, only 1,158 showed differences of >10%, and only 111 showed differences of >20%. Grozinger et a/.

~ - - - - a) ~ 1 000- .o u' 500- tn At O 1 2 1 2 3 4 Days of exposure to QMP Fig. 1. Dynamic regulation of gene expression in the honey bee brain by QMP. Bees were maintained in cages in the laboratory either with or without QMP. The number of cDNAs showing significant differences in expression on each day is shown. mRNA Quantification by Real-Time qRT-PCR. ConErmat~on of some of the results obtained from microarray analysis was performed with real-time qRT-PCR in individual brains (19) with an ABI Prism 7900 sequence detector and the SYBR green detection method (Applied Biosystems). Rp49 or eIF3-58, two housekeep- ing genes that did not vary in expression levels on these microarrays, were used as loading controls. Quantification was as described (19~. The sequences for the primers used are given in Table 4, which is published as supporting information on the PNAS web site. Results QMP Influences Brain Gene Expression in the Laboratory. There were 1,210 cDNAs with significantly higher expression and 1,397 cDNAs with significantly lower expression in the brains of QMP+ bees relative to QMP- bees. This is about eight times more than the number of false positives expected (25~. Several hundred cDNAs were significantly regulated on each day of the 4-day time course, with maximum numbers on days 2 and 3 and the fewest on day 1 (Fig. 14. The magnitude differences were smallest on day 1 as well: expression of only 3 ESTs changed by 40% on day 1, whereas 21, 20, and 21 ESTs, respectively, were regulated by 40% on the other three days. Expression levels for most cDNAs changed during the time course, but a small subset was chronically regulated across days 2, 3, and 4 (13 up-regulated and 6 down-regulated). Eight of these chronically regulated genes are annotated, with high sequence similarity to known Drosophila or human genes (Table 1~. They include the tran- scription factor Kr-hl (~28), the G protein-coupled receptor frizzled 2 (~29), and a transmembrane protein involved in regu- lating glial cell thickness (push/poe) (30~. See Table 5, which is published as supporting information on the PNAS web site, for a complete list of regulated genes. QMP-Mediated Gene Expression Correlates with Downstream Behav- ioral Effects. If QMP regulation of gene expression in the brain is related to the QMP-mediated delay in the transition from hive work to foraging (15), then the following pattern is predicted: exposure to QMP activates genes in the brain associated with nursing and represses genes associated with foraging. The pre- diction was tested by comparing our data with results from a previous study (14~. That study showed widespread differences in gene expression between nurses and foragers, with 1,360 showing significantly more mRNA abundance in nurse brains ("nurse list") and 1,310 significantly more mRNA abundance in forager brains ("forager listed. Results of this comparison agree with the prediction. A significantly larger proportion of QMP- up-regulated cDNAs was on the nurse list than were QMP- down-regulated cDNAs (Table 24. Likewise, a significantly larger proportion of QMP-down-regulated cDNAs were on the forager list than were QMP-up-regulated cDNAs. (Table 2~. These trends were even more striking if only the chronically regulated cDNAs are considered (Table 2~. See Table 5 for a complete listing of all QMP-regulated genes that are also on the nurse or foragers lists. QMP Influences Brain Gene Expression in Bee Colonies. There were 697 cDNAs that showed significant differences in brain expres- sion in bees sampled from QMP+ and QL colonies (Fig. 2~. Overall, these expression differences were most similar to the results from cages sampled on day 3. For example, of the cDNAs significantly up-regulated in the field, 59 were also significantly up-regulated in the cages (vs. 20 that were down-regulated in the cages), and of the cDNAs down-regulated in the field, 74 were down-regulated in cages (vs. 7 that were up-regulated in the cages). Relative to cage bees, there were fewer cDNAs with significant differences in colony bees, and they showed expres- sion differences of smaller magnitude. Among the genes signif- icantly regulated in the brain by QMP in both cage and colony Table 1. Annotated genes chronically regulated by QMP in the honey bee brain Closest Drosophila (or human) match Similarity score Fold difference QMP+/QMP- Possible function Nurse/forager Q9H2Y7 (human) CG14168 cit Traf l CG7474 poe frizzled 2 kr-h 1 2E-08 1E-13 5E-23 1 E-24 4E-85 9E-34 5E-96 1E-100 1.11 1.12 1.16 1.16 1.17 0.86 0.70 0.59 WD-repeat protein PDZ domain Carboxylesterase Tumor necrosis factor Forager receptor-associated factor Tubulinyl-tyrosine ligase Calmodulin binding, synpatogenesis G protein-coupled receptor Zn-finger transcription factor Nurse Nurse Forager Forager Genes found to be chronically regulated by QMP with high sequence similarity to known Drosophila or human genes are listed below. Similarity score: BLAST E value (this corresponds to the EST sequence only, except for Kr-hl, for which full sequence was obtained, and frizzled 2, for which additional sequence was identified from the genome project, http://h~sc.bcm.tmc.edu/blast/?organism=Amellifera). Fold difference column: the maximum difference between values obtained for bees maintained in cages with or without QMP. Nurse/forager column indicates in which behavioral group the gene was found to be significantly unregulated in an independent microarray-based study (14). Grozinger et al. PNAS 1 November25, 2003 1 vol. 100 1 suppl. 2 1 14521

Table 2. QMP activates genes in the bee brain associated with nursing and represses genes associated with foraging Location QMP Cage Total QMP Total QMP Chronically Chronically QMP QMP Cage and colony QMP QMP No. of cDNAs 1,397 1,210 6 13 374 323 59 74 % on % on forager fist nurse list 14 33 o 62 13 42 15 53 27 12 67 8 26 16 42 3 QMP-regulated cDNAs were compared to the lists of cDNAs significantly up-regulated in nurse bees or up-regulated in foragers. A significantly larger proportion of QMP ~ (up-regulated) cDNAs were on the nurse list than were QMP ~ cDNAs. Likewise, a significantly larger proportion of QMP ~ cDNAs were on the forager list than were QMP ~ cDNAs (P < 0.001, x2 tests). Genes chronically regulated by QMP showed the same trends. were: transcription factors HLH3B and klumpfuss, gap junction proteins inr2 and imp, Tor, a phosphatidylinositol 3-kinase, Nrv2, an Na+/K+ exchanging ATPase complex, RacGAP, a GTPase activator, and Rab6, a GTPase. As was the case in the laboratory experiments, a significantly larger proportion of QMP-up-regulated cDNAs were on the nurse list than were QMP-down-regulated cDNAs, and likewise for QMP-down-regulated cDNAs on the forager list (Table 2~. These trends were even more striking if only the cDNAs regulated in both the cages and colonies are considered (Table 2~. The field experiments also allowed us to compare the effects of a live queen to the effects of QMP on gene expression in the brain. A total of 1,047 cDNAs were differentially expressed between the OR and QMP colonies; thus, QMP did not com- pletely mimic the live queen. A total of 335 cDNAs were coregulated in the QR and QMP colonies relative to the QL colony; these genes may be specifically regulated by QMP released by the queen. QMP Effects on Transcription Factor. The gene with the biggest difference in mean expression levels in the cage experiments was 031 . y = 0.32x+0.011 R2= 0.16 .~.S-.4 ., ~-0.5 -0.3 ~ t^1 0 3 ~ IS. -0.3 Cage log2(QMP+/QMP] 0.5 ~F;g. 2. Comparison of QMP-regulated brain gene expression in bees from colonies in the field vs. cages in the laboratory. The cDNAs showing significant differences in expression in bees from QMP vs. QL (queenless) colonies are shown (minus three outliers, n = 694). The expression levels (log-transformed) of these cDNAs under colony and cage (day 3) conditions are plotted, and the regression line is shown. In general, cDNAs down-regulated in colony bees were down-regulated in cage bees, and likewise for up-regulated cDNAs. Expression differences were generally lower in colony bees. 14522 1 www.pnas.org/cgi/doi/10.1073/pnas.2335884100 Table 3. Effects of QMP on different functional categories of genes No. % Functional category annotated Regulated Protein phosphatases Synaptic vesicle transport lon channels Protein kineses Cytoskeletal organization and biogenesis Receptors Peptidases RNA-binding proteins Oxidoreductases Transcription factors 35 66 73 87 89 106 108 127 129 129 2.9 1.5 6.8 8.0 4.5 5.7 5.6 3.9 8.5 13.2 For each functional category, the number of genes significantly regulated by QMP (>10%) for at least 1 day in cage experiments are shown. Categories of molecular function are from the Gene Ontology Consortium; annotation is from ref. 16. a transcription factor, Kr-hl. Because transcription factors reg- ulate the expression of other genes, they may serve as markers for regulation of pheromone-mediated "transcriptional pro- grams" that control downstream behavioral effects. A total of 39 of the 129 cDNAs annotated as transcription factors (16) were significantly regulated by exposure to QMP (Table 6, which is published as supporting information on the PNAS web site), whereas 17 were significantly regulated by >10%. This propor- tion was relatively high compared with other functional catego- ries of genes (Table 3~. Microarray analysis showed that brain expression of three transcription factors (Kr-hl, Up, and klumpfuss) was significantly affected by QMP over more than 1 day (Fig. 3A). In the colony experiments, only Klumpfuss was significantly regulated. The cage results were verified with qRT-PCR, using individual bee MA 1.5 u' an _ ._ ~ 2, 1.0 ._ 2` 1.5 ct ._ `~5 1.0 - u) a, 0 5 at: cr oKr-h1 ·UTX nKlu D4 Colony B C · QMP- ~ 1.5 ° QMP+ il~lhl1 Klu Kr-h1 UTX Kr-h1 UTX Fig. 3. Confirmation of microarray results. mRNA levels for three transcrip- tion factors (kr-h1, utx, and klu) shown by microarray analysis to be signifi- cantly regulated by QMP were quantified by real-time qRT-PCR in individual brains. (A) Expression levels (QMP+/QMP- ratio) determined by microarray analysis on days (D) 1-4 for cage bees and colony bees. (B) Expression levels determined by qRT-PCR for bees exposed to QMP for 3 days from the same genotype as in A. Number of individually analyzed brains is indicated on bars. Data are means + SE (converted to the same arbitrary scale as the mean), normalized to the QMP- sample. Statistical analysis was done by one-tailed t test. (C) Same as B. except bees were from a second genotype. Grozinger et a/.

A in . ~ 2 - ._ Q - - a) 1.0 A 8 6 4 0.5 B 0 1 day old 6 · Foragers 0 1 day old L ~ Foragers Trial 1 Trial 2 Trial 1 Trial2 C 4 1O QMP- · QMP+ 1 Trial 1 Trial 2 Trial 3 Fig. 4. Behavior- and QMP-related Kr-hl expression in whole brains and mushroom bodies in the honey bee. mRNA levels of Kr-hl in 1-day-old bees and foragers were quantified with qRT-PCR in whole brains (A) and mushroom bodies (B) in two genotypes (trials 1 and 2). Differences were significant (P c 0.001, one-tailed ttest). (C) Effect of QMP on Kr-h1 mRNA levels in mushroom bodies. Differences were significant in trial 1 (P < 0.05) and trial 3 (P < 0.01) but not in trial 2 (P = 0.09). Other notations are as in Fig. 3. brains rather than samples of pooled brains (Fig. 3 B and C). In genotype R8 (Fig. 3B), which was the same as that used for the microarray studies, brain expression of Kr-hl and UP was significantly decreased and increased, respectively, in QMP+ bees, as in the microarray analyses, whereas klumpfuss levels were not significantly different. In a second genotype (Fig. 3C), Kr-hl brain expression again was significantly lower in QMP~ bees, but there was no effect of QMP on US expression levels. Because US was up-regulated for only 2 days in the microarray experiments, it is possible that its temporal pattern of QMP- mediated expression was different in this genotype. Regardless, Kr-hl clearly showed the most robust and consistent pattern of QMP regulation. Two additional experiments were conducted to further estab- lish Kr-hl as a candidate gene to study long-term, behaviorally relevant changes in brain gene expression caused by pheromone exposure. First, we determined whether QMP effects on Kr-hl expression in the brain were associated with behaviorally related differences in expression. Previous microarray studies indicated that Kr-hl expression is higher in foragers relative to nurses (14~. qRT-PCR analysis agreed, showing that brain Kr-hl expression was increased in foragers relative to 1-day-old bees (Fig. 44~. Second, we determined whether Kr-hl is expressed in the mushroom bodies, as a first step toward exploring the effects of pheromone on gene expression in brain regions involved in higher-order integration and processing. Kr-hl was expressed in the mushroom bodies, with expression significantly higher in foragers relative to 1-day-old bees (Fig. 4B) and also significantly higher in QMP- bees than QMP+ bees (Fig. 4C). Kr-hl expres- sion~ levels were not significantly different in optic lobes of QMP- vs. QMP+ bees (data not shown), suggesting that expres- sion of this gene is specifically regulated in the mushroom bodies rather than the whole brain. CloningA. mellifera kr-hl (GenBank accession no AY338499, see Fig. 5, which is published as supporting information on the PNAS web site) revealed that it contains eight zinc finger domains from amino acids 62-289 and Grozinger et al. has significant sequence similarity to the Drosophila Kr-hl protein and the partialAnophelesgambiae protein. There are two transcripts for Kr-hl present in Drosophila, Kr-hl RA and RB (28~. The RA transcript is present in larvae and adults, whereas the RB transcript is present only in embryos and has an addi- tional 55 aa on the N terminal. The clonedA. mellifera kr-hl does not contain this N-terminal extension, and thus matches the RA transcript most closely. However, it is ~200 aa shorter than the RA, because of deletions throughout the gene. · — Discussion This study has demonstrated that QMP causes changes in expression levels of many genes in the brain of adult honey bees, and that these changes correlate with some of the downstream behavioral effects of the pheromone. QMP effects on gene expression were detected both in a controlled laboratory envi- ronment and in bee colonies in the field, which represent a more natural environment. QMP causes transient changes in expres- sion of several hundred genes, but causes chronic changes in only a small subset of genes in the brain. The effects of QMP on brain gene expression changed over time. One possible explanation for this is that the transcriptional response to QMP is dynamic, with one set of genes activating/ repressing expression of another downstream set of genes in "transcriptional cascades" reminiscent of what occurs during Drosophila neural development (31~. These genes may only need to act transiently to produce the necessary response to queen pheromone, such as neuronal remodeling of pheromone- responsive networks. For example, bees raised in queenless conditions for 4 days have smaller synaptic structures in the antenna! lobe, suggesting that QMP may influence synaptic growth and remodeling during this time frame (12~. Thus, the dynamic nature of the response to QMP might be related to the fact that the bee's olfactory system continues developing for the first few days of adult life (32~. Alternatively, it simply might be difficult to detect small, but statistically significant, differences in gene expression across consecutive days, even with the relatively large number of replicates used in this study. In most cases, the observed signif- icant changes in gene expression were relatively subtle (~20%~. Perhaps the relatively small QMP-induced expression differ- ences are caused by effects of QMP on a small set of neurons. Small, but statistically significant, differences in gene expression are detectable in microarrays studies such as ours with numerous replicates (14, 27) and can have biological significance (26, 27~. Some genes chronically regulated by QMP may be involved in stably altering neuronal activity and responsiveness. For exam- ple, one of the chronically down-regulated genes encodes a homolog of the Drosophila protein Pushover (also named Poe), which has been shown to play a role in regulating glial cell thickness (30) and neuronal excitability (334. Such alterations in central brain processing regions could lead to changes in re- sponsiveness to various stimuli, thereby altering behavior (34~. There was considerable overlap in the genes regulated by QMP in the cages and in colonies, but gene expression changes in the colonies were smaller and involved fewer genes. This might be because the "QMP strip" used in the colony releases a lower amount of pheromone per bee than the glass slide in the cages; thus, the colony bees may have been exposed to an almost 2-fold lower dose of QMP (K. N. Slessor, personal communication). Another factor is that the colony environment is more varied with respect to pheromonal and other stimuli. In particular, the brood in the colonies release a pheromone that produces many of the same effects as QMP (35-38), and this may have atten- uated the response to QMP in the colony experiment. If so, then the set of genes that were found to be regulated in both the colony and the cage experiments may be robustly regulated by or PNAS | November25, 2003 1 vol. 100 1 suppl. 2 | 14523

only sensitive to QMP. Further cage experiments using brood pheromone can help address these questions. QMP and a live queen had similar effects on some, but not all, genes. This finding is consistent with observations showing that QMP is not as effective as a full queen extract in producing behavioral and physiological responses. For example, an addi- tional four components were recently identified that improve the performance of synthetic queen pheromone in the attraction of workers to the queen, and even this nine-component blend is not quite as effective as the full extract (9~. The genes that were specifically regulated only under queenright conditions may be responding to other unidentified components of queen phero- mone and may prove to be reliable markers for future elucidation of a more complete pheromone blend. QMP consistently activated genes correlated with nursing behavior and repressed genes correlated with foraging behavior, in both cage and colony experiments. This finding suggests that the effects of QMP on the timing of the transition from working in the hive to foraging (15) may be caused by QMP regulation of genes in the brain that produce these behavioral states. At least some QMP-regulated genes may be involved in regulating the transitions to nursing and foraging, rather than the maintenance of these states, because the bees we used were too young or simply unable to perform these behaviors in laboratory cages. The fact that many QMP-regulated genes were not found to be associated with nursing or foraging behavior may reflect the fact that QMP also is involved in the regulation of several other behavioral and physiological processes besides age-related divi- sion of labor, such as inhibiting ovary development and the rearing of new queens. Further microarray experiments may identify distinct transcriptional programs that relate to other pheromone-regulated processes. The proportion of transcription factors regulated by QMP was relatively high compared with other functional groups of genes. This result suggests transcription factors may be important targets of pheromone activation. To aid in the future identification of specific transcriptional programs, we catalogued the transcription factors whose expression levels were significantly regulated by QMP. Only one transcription factor was found to be chronically regulated; most showed significant changes in expression on only 1 day. Transiently regulated transcription factors may simply initiate a downstream program and be subsequently turned off in a matter of hours as is the case for CREB (cyclic AMP-response element binding protein), which initiates changes in neuronal plasticity (reviewed in refs. 39 and 40~. Kr-hl was the most highly and robustly regulated gene iden- tified in this study. Furthermore, Kr-hl has the unique trait of being chronically regulated by a pheromone. Kruppel homologs are zinc finger transcription factors that play important roles in orchestrating development and cell differentiation (reviewed in (17), including neural development (31~. Kr-hl in particular was 1. Dulac, C. & Torello, A. T. (2003) Nat. Rev. Neurosci. 4, 551-562. 2. Vosshall, L. B. (2001) Chem. Senses 26, 207-213. 3. Halem, H. A., Baum, M. J. & Cherry, J. A. (2001) J. Neurosci. 21, 2474-2480. 4. Brennan, P. A., Schellinck, H. M. & Keverne, E. B. (1999) Neuroscience 90, 1463-1470. 5. Free, J. B. (1987) Pheromones of Social Bees (Cornell Univ. Press, Ithaca, NY). 6. Slessor, K. N., Kaminski, L.-A., King, G. G. S., Borden, J. H. & Winston, M. L. (1988) Nature 332, 354-356. 7. Winston, M. L. & Slessor, K. N. (1998) Apidologie 29, 81-95. 8. Winston, M. L. (1987) The Biology of the Honey Bee (Harvard Univ. Press, Cambridge, MA). 9. Keeling, C. I., Slessor, K. N., lIigo, H. A. & Winston, M. L. (2003) Proc. Natl. Acad. Sci. USA 100, 4486-4491. 10. Hoover, S. E. R., Keeling, C. I., Winston, M. L. & Slessor, K. N. (2003) Naturwissenschafterz 90, 477-480. 11. Winston, M. L., Higo, H. A., Colley, S. J., Pankiw, T. & Slessor, K. N. (1991) J. Insect Behav. 4, 649-660. 14524 1 www.pnas.org/cgi/doi/10.1073/pnas.2335884100 identified as an ecdysone-sensitive transcript during Drosophila morphogenesis (28), and in a gain-of-function screen for genes involved in motor axon guidance and synaptogenesis in Drosoph- ila larvae (41~. Differences in expression patterns and sequence divergences within the DNA-binding regions of Kruppel-like proteins across mammalian lineages suggest that members of this family have undergone duplication and acquired novel functions in different species during evolution (42~. The A. mellifera Kr-hl protein is highly similar to Drosophila Kr-hl and the Anopheles gambaie ortholog, suggesting that it functions similarly in all three insects. However, in the case of the honey bee, a species with a highly derived form of social organization, it has evolved to be regulated by a pheromone, perhaps in addition to intrinsic factors common to the dipteran species with solitary lifestyles. QMP regulation of Kr-hl occurs in the mushroom bodies, the sites of integration of sensory information, so Kr-hl may be involved in organizing stable changes in gene expression and neuron structure that are necessary to transduce the chemosensory QMP stimulus to downstream changes in behavior and physiology. Further exper- iments will be necessary to map Kr-hl expression throughout the brain to further elucidate the function of Kr-hl in response to pheromone. Given that Kr-hl is strongly down-regulated by QMP, it is puzzling that Kr-hl is repressed by QMP in young honey bees but up-regulated in older bees, because both groups were taken from colonies with a queen. Perhaps this is because foragers typically contact the queen less than do younger bees, or foragers are simply less responsive to QMP. Further experi- ments will be needed to explore this issue. QMP affects the expression of many genes in the bee brain, and in particular changes expression of genes associated with behaviors that also are regulated by this pheromone. Some effects on gene expression are relatively transient, which may reflect short-term modifications in synaptic plasticity, and some are more chronic, which may reflect long-term chan~,es in neuronal responsiveness and behavioral state. Some of the genes identified here may represent transcriptional programs regulat- ing particular pheromone-mediated physiological and behav- ioral processes. Further genomewide analysis of the transcrip- tional effects of QMP and other pheromones should lead to new insights into how pheromones regulate social life. We thank K. Pruiett for expert ass~stance with the bees; A. Barron, C. Schook, and L. Wraight for technical assistance; R. Velarde for samples of 1-day-old and forager bees; S. Rodriguez-Zas for help with statistical analysis; M. Band for fabricating microarrays of outstanding quality; C. Keeling, S. Hoover, K. N. Slessor, and M. L. Winston for helpful advice; and R. Maleszka and members of the Robinson laboratory for comments that improved the manuscript. I~his work was supported by a Beckman Institute postdoctoral fellowship (to C.M.G.), a National Science Foun- dation Bioinformatics postdoctoral fellowship (to C.W.W.), and grants from the Burroughs Welcome Trust, the National Institutes of Health, and the U.S. Department of Agriculture (to G.E.R.~. 12. Morgan, S. M., Butz Huryn, V. M., Downes, S. R. & Mercer, A. R. (1998) Behav. Brain Res. 91, 115-126. 13. Robinson, G. (2002) Am. Nat. 160, S160-S172. 14. Whitfield, C. W., Cziko, A.-M. & Robinson, G. (2003) Science 302, 296-299. 15. Pankiw, T., Huang, Z.-Y., Winston, M. L. & Robinson, G. E. (1998) J. Insect Physiol. 44, 685-692. 16. Whitfield, C. W., Band, M. R., Bonaldo, M. F., Kumar, C. G., Liu, L., Pardinas, J. R., Robertson, H. M., Soares, M. B. & Robinson, G. E. (2002) Genome Res. 12, 555-566. 17. Kaczynski, J., Cook, T. & Urrutia, R. (2003) Genome Biol. 4, 206.1-206.8. 18. Laidlaw, J., H. H. (1987) Bee World, 17-38. 19. Ben-Shahar, Y., Robichon, A., Sokolowski, M. B. & Robinson, G. E. (2002) Science 296, 741-744. 20. Ledoux, M. N., Winston, M. L., Higo, H. A., Keeling, C. I., Slessor, K. N. & Le Conte, Y. (2001) Insectes Soc. 48, 14-20. 21. Veltuis, H. H. W. (1970) Entolmol. Exp. Appl. 13, 377-394. 22. Schulz, D. J. & Robinson, G. E. (1999) J. Comp. Physiol. A 184, 481-488. Grozinger et a/.

23. Kerr, M. K. & Churchill, G. A. (2001) Genet. Res. 77, 123-128. 24. Hegde, P., Qi, R., Abernathy, K., Gay, C., Dharap, S., Gaspard, R., Hughes, J. E., Snesrud, E., Lee, N. & Quackenbush, J. (2000) Bio Techniques 29, 548-550, 552-554, 556. 25. Townsend, J. P. & Hartl, D. L. (2002) Genome Biol. 3, 0071.1-0071.6. 26. Yan, X. D., Hanson, A. J., Nahreini, P., Koustas, W. T., Andreatta, C. & Prasad, K. N. (2002) In Vitro Cell Dev. Biol. Mom. 38, 529-537. 27. Gibson, G. (2002) Mol. Ecol. 11, 17-24. 28. Pecasse, F., Beck, Y., Ruiz, C. & Richards, G. (2000) Dev. Biol. 221, 53-67. 29. Bhanot, P., Brink, M., Samos, C. H., Hsieh, J. C., Wang, Y., Macke, J. P., Andrew, D., Nathans, J. & Nusse, R. (1996) Nature 382, 225-230. 30. Yager, J., Richards, S., Hekmat-Scafe, D. S., Hurd, D. D., Sundaresan, V., Caprette, D. R., Saxton, W. M., Carlson, J. R. & Stern, M. (2001) Proc. Natl. Acad. Sci. USA 98,10445-10450. 31. Isshiki, T., Pearson, B., Holbrook, S. & Doe, C. Q. (2001) Cell 106, 511-521. 32. Pham-Delengue, M. H., Trouiller, J., Caillaud, C. M., Roger, B. & Masson, C. (1993) Apidologie 24, 267-281. Grozinger et a/. 33. Richards, S., Hillman, T. & Stem, M. (1996) Genetics 142, 1215-1223. 34. Beshers, S. N., Robinson, G. E. & Mittenthal, J. E. (1999) in Information Processing in Social Insects, ed. Detrain, C. (Birkhauser, Boston), pp. 115-139. 35. Arnold, G., Le Conte, Y., Trouiller, J., Hervet, H., Chappe, B. & Masson, C. (1994) C. R. Acad. Sci. Ser. III 317, 511-515. 36. Le Conte, Y., Areski, M. & Robinson, G. E. (2001) Proc. R. Soc. London Ser. B 268, 1-6. 37. Mohammedi, A., Crauser, D., Paris, A. & Le Conte, Y. (1996) C. R. Acad. Sci. Ser. III 319, 769-772. Mohammedi, A., Paris, A., Crauser, D. & Le Conte, Y. (1998) Natunvissen- schaften 85, 455-458. 39. Clayton, D. F. (2000) Neurobiol. Learn. Mem. 74, 185-216. 40. West, A. E., Griffith, E. C. & Greenberg, M. E. (2002) Nat. Rev. Neurosci. 3, 921-931. 41. Kraut, R., Menon, K. & Zinn, K. (2001) Curr. Biol. 11, 417-430. 42. Shannon, M., Hamilton, A. T., Gordon, L., Branscomb, E. & Stubbs, L. (2003) Genome Res. 13, 1097-1110. PNAS 1 November25, 2003 1 vol. 100 1 suppl. 2 1 14525

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One major goal of post-genomic biology is to understand the function of genes. Many gene functions are comprehensible only within the context of chemical communication, and this symposium seeks to highlight emerging research on genomics and chemical communication and catalyze further development of this highly productive interface. Many of the most abundantly represented genes in the genomes characterized to date encode proteins mediating interactions among organisms, including odorant receptors and binding proteins, enzymes involved in biosynthesis of pheromones and toxins, and enzymes catalyzing the detoxification of defense compounds. Determining the molecular underpinnings of the component elements of chemical communication systems in all of their forms has the potential to explain a vast array of ecological, physiological, and evolutionary phenomena; by the same token, ecologists who elucidate the environmental challenges faced by the organisms are uniquely well-equipped to characterize natural ligands for receptors and substrates for enzymes. Thus, partnerships between genome biologists and chemical ecologists will likely be extremely synergistic. To date, these groups have rarely had opportunities to interact within a single forum. Such interactions are vital given the considerable practical benefits potentially stemming from these studies, including the development of biorational products for agricultural and forest pest management, for disease treatment, and for improving the quality of ecosystem health.

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