Abstract
The aryl hydrocarbon receptor (AHR) mediates dioxin toxicities. Several studies have suggested that two amino acid residues corresponding to the 324th and 380th positions in the ligand binding domain (LBD) of the chicken AHR1 (Ile_Ser as high sensitivity, Ile_Ala as moderate sensitivity, and Val_Ala as low sensitivity), could be an important factor determining dioxin sensitivity in avian species. Here, we analyzed the association between ecological factors and AHR1 LBD genotypes of 113 avian species. Cluster analyses showed that 2 major clusters and sub-clusters of the cluster 3 were associated with specific AHR1 genotypes depending on the food, habitat, and migration of the animal. The majority of the species with Ile_Ala type were the Passeriformes, which are omnivorous or herbivorous feeders in the terrestrial environment. The species with Val_Ala type was primarily composed of raptors and waterbirds, which have been exposed to naturally occurring dioxins. An in vitro reporter gene assay revealed that the sensitivity to a natural dioxin, 1,3,7-tribromodibenzo-p-dioxin was in the order of Ile_Ser > Ile_Ala > Val_Ala. These results suggest that ecological factors related to the exposure of natural dioxins contribute to natural selection of the avian AHR1 genotype, which consequently leads to different sensitivity to man-made dioxins.
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Introduction
Contamination with dioxin-like compounds (DLCs), including polychlorinated dibenzo-p-dioxins, polychlorinated dibenzofurans (PCDD/Fs), and coplanar polychlorinated biphenyls (PCBs), are of great environmental concern due to their widespread presence in the ecosystem and high toxicity to humans and wildlife1,2. After exposure to DLCs, some avian species, such as fish-eating birds, have suffered from reproductive impairment due to a high incidence of embryonic mortality and edema. These species also had developmental abnormalities, including feather loss, crossbill, maldeveloped limbs, and supernumerary digits. As a result of these adverse effects, DLCs caused severe declines of some avian populations in the Great Lake region of North America3,4,5,6.
Toxic effects of DLCs are mediated by a ligand-dependent nuclear transcription factor, the aryl hydrocarbon receptor (AHR), which is a member of the basic-Helix-Loop-Helix (bHLH) and Per-Arnt-Sim (PAS) family of proteins. In the absence of a ligand, AHR is stable due to interactions with chaperones, including two molecules of heat shock protein 90 (Hsp90), prostaglandin E synthase3 (p23), and the immunophilin-like protein hepatitis B virus X-associated protein 2 (XAP2) in the cytosol7. Upon binding with ligands like DLCs, the AHR relocates to the nucleus to form a heterodimer with its partner molecule, aryl hydrocarbon receptor translocator (ARNT). The ligand-bound AHR eventually transactivates cytochrome P450 1 A (CYP1A) and other genes by binding to a specific dioxin-responsive element, which has a core sequence of 5′-TNGCGGTG-3′ located in the promoter region of these target genes8. Induction of CYP1A is thus considered to be an indicator of AHR activation after exposure to DLCs9.
The basic molecular mechanism of the AHR-mediated signaling pathway is evolutionarily conserved in avian species as well as mammals. Although mammals have only a single AHR, birds have at least two AHR isoforms, AHR1 and AHR210,11. Despite the evolutionary conservation of the AHR-mediated signaling pathway in birds, earlier in vitro and in vivo studies have reported large interspecies differences in sensitivity to exposure to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) and other DLCs12,13. Some previous studies have suggested that an in vitro assay system constructed using AHR expression vectors from chicken and other avian species may be a valuable tool for evaluating interspecies differences in responses to DLCs, and consequently for assessing risks for the species concerned14,15,16,17,18.
The varying degrees of TCDD sensitivity in avian species have been explained by sequence differences in the ligand binding domain (LBD) of avian AHR1s, specifically two amino acid residues corresponding to Ile-324 and Ser-380 in the chicken AHR1 (ckAHR1)19. Three genotypes divergent at the corresponding sites have been found in avian AHR1 orthologs. The AHR1 LBD genotype is classified into high (Ile_Ser), moderate (Ile_Ala), and low sensitivity types (Val_Ala)13,19. In previous studies, we have shown that the black-footed albatross AHR1 (bfaAHR1) has Ile-325 and Ala-381 at the corresponding sites, and the common cormorant AHR1 (ccAHR1) has Val-325 and Ala-38114,15,16. The TCDD-EC50 values for AHR1-mediated transactivation were in the order of ckAHR1 (0.030 nM) < bfaAHR1 (0.077 nM) < ccAHR1 (0.36 nM) as expected from the AHR1 genotype. Furthermore, in silico docking simulations of avian AHR1 and TCDD interactions suggested that the thermodynamic stability of the two amino acid residues involved in the interaction with TCDD reflect the sensitivity to TCDD in these avian species20.
It has been reported that sensitivity to DLCs in avian species may be AHR1 dependent, due to the excessive amount of mRNA detected compared to other isoforms15,16,21. This implies that the three AHR1 genotypes have been subjected to natural selection in avian species; however, whether their presence can be completely attributed to natural selection in avian species during evolution and what ecological factors might have contributed to selection are still unknown.
Here, we hypothesize that ecological factors have driven natural selection pressures on AHR1 genotypes in the evolutionary process of avian species, and eventually have led to the interspecies differences in the sensitivity to DLCs. To address these questions, we investigated the amino acid sequences of AHR1 LBDs of 14 Far East avian species. We statistically analyzed the association between ecological factors and avian AHR1 LBD genotypes by the combination of two-way cluster analysis and nonmetric multidimensional scaling (NMDS) in these AHR1 LBD sequences as well as those of 99 avian species deposited in GenBank. In the present study, we explored the ecological factors that may have affected the selection of AHR1 genotypes in avian species.
Results
Sequence analysis of avian AHR1 LBD amino acids
The cDNAs of AHR1 LBDs from the blood and liver samples of 14 Far East species were sequenced. Among the 14 species examined, the AHR1 from 13 of the species was classified as a moderately sensitive type (Ile_Ala), with only the grey-headed woodpecker harboring a sequence type associated with low sensitivity (Val_Ala) (Fig. S1). To enhance our sample size, the AHR1 amino acid sequences of 99 additional avian species were obtained from Genbank (Table S1).
We examined a total of 113 species belonging to 21 of the 40 extant avian orders22 as classified by the International Ornithological Congress (IOC). The Passeriformes comprised 39.8% of the total species included in the present study. Considering that Passeriformes is the largest order of avifauna, which consists of approximately 50% of the 10,000 bird species known, the species composition of our samples was considered appropriate in order to analyze the selection pressures on AHR1 genotypes by ecological factors.
All of the 113 avian AHR1 genotype profiles were classified into three sensitivity types according to their amino acid sequences (Ile_Ser, Ile_Ala, and Val_Ala types), which correspond to the 324th and 380th amino acid positions in ckAHR1. The classification demonstrated that of the 113 species, the highly sensitive Ile_Ser type accounted for 4.4% of amino acid sequences analyzed. Considering that this highly sensitive type was a minority of the avian AHR1 genotypes, birds with this genotype may have a disadvantage when adapting to the environment in comparison to the other genotypes. The Ile_Ala and Val_Ala types accounted for 56.6% and 39.0% of all species, suggesting that these two types are ubiquitous AHR1 genotypes in avian species.
To determine the extent of sequence conservation of the AHR1 LBD among the avian species, CLUSTALW was used to construct pairwise amino acid alignments for each AHR1 genotype (Fig. S2). The percentage identity among AHR1 LBD amino acid sequences was 95~100% in the Ile_Ser type, 93~100% in the Ile_Ala type, and 99~100% in the Val_Ala type. In the alignment of the Ile_Ser type, there were five substitutions at sites corresponding to the 297th, 298th, 305th, 337th, and 387th amino acid residues (Fig. S2A). Of these sites, the 297th, 298th, and 387th amino acid residues comprised a portion of the β-sheet structure, whereas the 305th and 337th were involved in the α-helix (Fig. S3A). In the case of the Val_Ala type, only one mutation was found at the 360th site in the Humboldt penguin AHR1 (Fig. S2B). This amino acid residue forms part of the β-sheet structure, but is not a component of the ligand binding cavity, suggesting that this mutation does not affect sensitivity to DLCs (Fig. S3C). In the Ile_Ala type alignment, five mutations at sites corresponding to the 297th, 304th, 337th, 362nd, and 387th amino acids in the homology model of the black-tailed gull AHR1 were identified (Fig. S3B) and an insertion of five amino acids was found in the swan goose AHR1 (Figs S2C and S3D).
Phylogenetic analysis of avian AHR1 LBD
The phylogenetic tree of AHR1 LBD is divided into two clusters according to genotype (Fig. S4). The first clade includes waterbirds (ducks, herons, cormorants, and gulls) and raptors (owls, hawks, vultures, and ospreys), which mainly harbor the Val_Ala type (species shaded blue in Fig. S4). The second clade is mainly composed of passerines, pheasants, and quails, which have the Ile_Ala type sequence (species shaded yellow in Fig. S4). Although the Ile_Ser type has a scattered distribution in this phylogeny, the major clusters are mainly divided between the Ile_Ala and Val_Ala type. Thus, the results demonstrate that these two amino acids have played a critical role in the evolution of the avian AHR1 LBD.
To understand the distribution of avian AHR1 genotypes as it relates to the traditional classification of birds, information on AHR1 genotypes of the 113 species was given in the phylogenetic tree constructed by Prum et al. (Fig. 1)23. The result demonstrates that particular AHR1 genotypes are dominant in certain avifauna groups. The moderately sensitive Ile_Ala type was dominant in the Phasianidae of the Galliformes, the Scolopacidae of the Charadriiformes, and the Passeriformes (species shaded green in Fig. 1). The low sensitivity Val_Ala type was dominant in the Anatidae of the Anseriformes, the Phalacrocoracidae of the Suliformes, the Charadriiformes (excluding the Scolopacidae), the Accipitriformes, the Strigiformes, the Falconiformes, the Coraciiformes, and the Piciformes (species shaded blue in Fig. 1). For the highly sensitive Ile_Ser type, no preference to order was observed (species shaded red in Fig. 1). Thus the acquisition of a specific AHR1 genotype in the species, which are evolutionarily close and share similar ecological conditions, may be advantageous for survival and evolutionary adaptation.
Composition of ecological factors
To understand the contribution of ecological factors to the acquisition of the avian AHR1 genotype, we analyzed the composition of various ecological factors for each species using a cross tabulation test (Fig. S5). Each AHR1 genotype was composed of different proportions of ecological factors related to habitat (χ2 = 60.975, p < 0.001) and food types (χ2 = 50.625, p < 0.001), except for the Ile_Ser type due to its small sample size (4% of all species) (Fig. S5).
For the habitat type, 62% of the Val_Ala type species inhabit the aquatic environment, which includes wetlands, as well as marine coastal, supratidal, and neritic areas (Fig. S5A). The terrestrial environment (forests, shrublands, and grasslands) was a major habitat for the species of both the Ile_Ala and Ile_Ser types, accounting for over 60% of all animals sampled. These were the most distinct results describing species proportions in habitat type distribution according to the AHR1 genotype (χ2 = 60.975, p < 0.001). For the food type, Val_Ala type species were composed of more various feeding habits than those in other genotype species. Over 50% of Val_Ala species showed carnivorous feeding habit, including invertebrates, vertebrates, and aquatic arthropods (Fig. S5B), while the species with other genotypes were dominantly omnivorous feeders (χ2 = 50.625, p < 0.001). Concerning the migration type (Fig. S5C), the migratory species were mainly characterized by the Ile_Ala and Val_Ala types. The migratory species in these genotypes were present in similar levels (χ2 = 5.449, p > 0.05). Analysis of nesting patterns showed no distinct relationship with AHR1 genotypes (χ2 = 20.775, p > 0.05) (Fig. S5D). Collectively, the cross tabulation analysis demonstrated that habitat and food patterns had significant relationships with the AHR1 genotypes; however, the results from the analysis of the Ile_Ser type data were unreliable due to the small sample size.
Relationship between ecological factors and AHR1 genotypes
The relationships between ecological factors and the AHR1 genotypes were investigated using a two-way cluster analysis and NMDS. In the two-way cluster dendrogram, the ecological factors were classified according to similarities in the configuration of species group (Fig. 2). Cluster A includes the forest habitat and omnivorous feeding type, as well as tree nesting and migration types, with the most represented species from the Passeriformes. Cluster B includes the ecological factors of water birds which are ground-nesting and non-migratory species, and consisted of food types, including invertebrates, fish, and aquatic arthropods, as well as the wetland, marine coastal, and supratidal habitat types. Cluster C was composed of a variety of ecological factors including plant feeding, occasionally migration, and nesting in tree cavities as well as cliffs, buildings and scrub. These clustering patterns demonstrate that ecological factors have high mutual dependency and are closely related to each other.
In the two-way cluster analysis, two main clusters (cluster 1 and 2) and three sub-clusters (cluster 3-1, 3-2, and 3-3) of avian species were grouped according to the similarity of ecological factors. We investigated the major factors of each cluster to explain the relationship between the AHR1 genotypes and ecological factors, based on equal probability (Figs 3 and 4). The birds in cluster 1 primarily inhabit wetland or marine environments and feed on fish, aquatic arthropods or plants, thus aquatic habitats are the primary ecological factor for this group. A majority (74%) of the species examined in cluster 1 have the low sensitivity AHR1 genotype (Val_Ala type). Water birds (heron, duck, goose, cormorant, gull, and penguin) and a piscivorous raptor, the osprey, are also a part of this cluster (Table 1). Avian species from cluster 2, 3-2, and 3-3 inhabit inland regions including forests, shrublands, and grasslands. The migratory type is the main factor accounting for the differential grouping of cluster 2 and 3. Cluster 2 mainly consists of migratory birds, which inhabit forests or shrublands and are omnivorous, insectivorous, and herbivorous species. The moderately sensitive Ile_Ala AHR1 genotype was found in 72% of the species in this cluster that belong to the passerine group (Table 1). Cluster 3 consists of non-migratory or short-distance migratory birds and is further divided into 3 sub-clusters. Compared to the other groups, sub-cluster 3-1 is composed of the species with the most variable food types, including terrestrial invertebrates, terrestrial vertebrates, fish, and aquatic invertebrates. The animals in this group, including raptors, kingfishers, and crows (Table 1), share vertebrates as a common food type and 90% of them have the Val_Ala type AHR1. Sub-cluster 3-2 contains omnivorous species that inhabit shrubland and occasionally migrate, with a total of 82% of these species sharing the Ile_Ala type sequence (Table 1). Additionally the passerines, which occasionally migrate, are also part of this sub-cluster. The species of sub-cluster 3-3 are omnivorous and non-migratory and include pheasants, quails, and non-migratory passerines which are mainly composed of Ile_Ala (68%) genotype representatives. Interestingly, the proportion of species with the Ile_Ser type was higher in this cluster than in the others (Fig. 2 and Table 1).
In order to further verify our results, the NMDS was conducted on the ecological factor and avian AHR1 genotype datasets. The data accounted for 79% of the distribution along axis 1 and 2 and was statistically significant (p < 0.05). Each colored circle in Fig. 5 represents the clusters to which each species belongs as shown by the cluster analysis. Species in cluster 1 were distinguished by marine and wetland ecosystem factors, and the terrestrial species were divided into three clusters according to 4 ecological factor categories (Table S2). Thus data distribution along the two axes of the NMDS were consistent with the results of two-way cluster analysis (Fig. 5).
Response of AHR1 genotypes to a naturally occurring dioxin
This study reveals that certain avifauna groups favor particular AHR1 genotypes from phylogenetic and ecological factor analyses. In particular, waterbirds and raptors with a low sensitive Val_Ala AHR1 genotype might have a selective advantage under conditions that the high exposure level to naturally occurring dioxins continuously takes place in the environment; the exposure to these natural dioxins may be a natural selection pressure of the AHR1 genotype in avian species. To examine this assumption, we compared the transactivation potencies of three AHR1 genotypes (ckAHR1: Ile_Ser type, bfaAHR1: Ile_Ala type, and ccAHR1: Val_Ala type) by the exposure to a naturally occurring dioxin, 1,3,7-tribromodibenzo-p-dioxin (1,3,7-TriBDD) in in vitro reporter gene assay. The result showed that the Ile_Ser type had the lowest LOEC value (1.2 nM), followed by Ile_Ala type (12 nM) and Val_Ala type (120 nM) (Fig. 6).
Discussion
We initially compared the amino acid sequences of AHR1 LBDs of 113 avian species. The results showed that only a few mutations were identified between the species with the same AHR genotypes. An earlier study focused on site-directed mutagenesis of avian AHR1s demonstrated that the Ile-324 and Ser-380 of ckAHR1, and Val-325 and Ala-381 of the common tern AHR1 are critical sites involved in the binding of TCDD to AHR119. An in vitro chimeric AHR1 reporter gene assay proved that four of the variable sites, other than Ile/Val-324/325 and Ser/Ala-380/381, do not change the transactivation potency of AHR1 by dioxin exposure24. Furthermore, our in silico simulation of the molecular dynamics of AHR1 also supports the assumption that these two amino acids are critical in the interaction with TCDD20. In case of the five insertions in the sequences of swan goose AHR1, the insertions are not located in the region that interacts with TCDD20; therefore, they should also not affect the sensitivity to DLCs in the species harboring Ile_Ala type sequences. Collectively, AHR1-mediated dioxin sensitivity can be determined by sites corresponding to 324th and 380th amino acid residues of ckAHR1, including the Ile_Ser, Ile_Ala, and Val_Ala types.
Recently, involvement of AHR in physiology such as immune system maintenance, protein degradation, and cell proliferation has been elucidated25,26. In adaptive immunity, AHR plays a pivotal role in anti-bacterial defense27 and disease tolerance to xenobiotics28,29. Due to the promiscuous nature of the binding pocket, AHR can be activated by various ligands not only polycyclic aromatic hydrocarbons (PAHs) and DLCs but also those that are naturally derived, including tryptophan metabolites30 and bacterial pigments27. FICZ (6-formylindolo [3,2-b] carbazole) is a tryptophan metabolite and has a high affinity to AHR31,32. Recent studies have shown that transactivation potencies of FICZ are greater than TCDD regardless of the avian AHR1 genotype20,33. In addition, there are fewer inter-species differences in AHR1 sensitivity to this endogenous ligand33, whereas there are large differences in responses to TCDD of the AHR1 among species20,24. Our previous study also supported that there was no linkage between avian AHR1 genotypes and AHR1-mediated responses to FICZ34. This implies that the exposure to naturally occurring dioxins under various ecological conditions has exerted selection pressure on the AHR1 genotype with different dioxin sensitivity in the evolutionary process of avian species. To prove this assumption, we analyzed the relationship between ecological factors and avian AHR1 genotypes.
An earlier study demonstrated that the genotype distribution of key amino acids, corresponding to the 324th and 380th amino acid positions of ckAHR1, in avian AHR isoforms could not be predicted from the phylogenetic tree or previously constructed taxonomy35. On the other hand, when we investigated the genotype distribution using our larger data set of 113 avian species, certain AHR1 genotypes were dominant in the Neoaves. The majority of the passerine have a moderately sensitive Ile_Ala AHR1 genotype, whereas waterbirds and raptors have a less sensitive Val_Ala AHR1 genotype. The species with the Val_Ala AHR1 genotype are in high trophic positions of the food web, which feed on fish, invertebrates, and vertebrates, and could have been exposed to high levels of various naturally synthesized dioxins. The species with a moderately sensitive Ile_Ala AHR1 genotype tend to be omnivorous feeders and mainly inhabit terrestrial ecosystems (Fig. 2). Since most passerines live on land, the terrestrial ecosystem is a major contributing factor to the preference for this genotype.
When we compare the previously reported sequences of various vertebrates including fish, birds and mammals, Ile_Ala type is the most common genotype. Therefore we assume that Ile_Ala type may be a primary genotype in vertebrates. Recent studies have reported that natural sources of dioxins exist in the terrestrial36 and aquatic ecosystem37. Naturally occurring dioxins in terrestrial ecosystem included 1,3,6,8- and, 1,3,7,9-tetrachlorodibenzo-p-dioxins, and 2,4,6,8-tetrachlorodibenzofuran, of which the congener profile differs from that of anthropogenic sources38. These congeners are synthesized when 2,4-dichlorophenol is allowed to react with the fungal enzyme chloroperoxidase in the slime mold, Dictyostelium purpureum39, and lichens, Lecanora cinereocarnea40 and Lecanora iseana41. In the marine ecosystem, notable concentrations of polybrominated dibenzo-p-dioxins (PBDDs) including 1,3,7-TriBDD have been detected in Baltic Sea biota37. It has been suggested that some PBDD congeners are synthesized in red algae by UV irradiation of hydroxylated polyborminated dipheyl ethers (OH-BDE)42. These naturally synthesized dioxins could be assimilated by filter feeders like mussels, and then transferred to mussel-eating fish, e.g., perch37,43. Given these findings, it is possible that raptors and waterbirds have been exposed to high levels of naturally occurring dioxins in the process of evolutionary adaptation. Thus this might be a driving force to differentiate AHR1 genotypes. In this study, we examined this hypothesis by using an in vitro reporter gene assay where each of three AHR1 genotypes was expressed in COS-7 cells treated with a natural dioxin, 1,3,7-TriBDD. The results revealed that the sensitivity to the natural dioxin was in the order of Ile_Ser > Ile_Ala > Val_Ala as expected (Fig. 6). Therefore, the acquisition of Val_Ala AHR1 genotype in waterbirds and raptors might be due to the high exposure levels of natural dioxins to mitigate the toxicity of natural dioxins. The highly sensitive Ile_Ser AHR1 genotype was found only in five species, implying that this type is rare in birds. Although it is still unclear how this genotype affects avian adaptation, its rarity suggests that it could be disadvantageous or perhaps impart a selective competition advantage to a few selected species.
Previous studies have found that the function of specific genes can be altered according to the environment, as is the case with heat shock proteins44. It is well known that the aggregate or high constitutive expression level of heat shock protein 70 in thermophilic species leads to its heat resistance45. Likewise, an AHR1 genotype in avian species might be preferred in a certain common environment such as the exposure to naturally occurring dioxins, and this could be beneficial to their fitness. Here, we hypothesized that differential sensitivity to DLCs in avian species may be due to various AHR1 genotypes that have evolved under unique environmental circumstances. In conclusion, this study suggests that the exposure to natural dioxins could have enforced natural selection pressure on avian AHR1 genotypes, which consequently led to different sensitivities to man-made dioxins.
Materials and Methods
Collection of avian AHR1 LBD amino acid sequences
The AHR1 LBD amino acid sequences of 99 avian species reported in previous studies were obtained from the GenBank database (Table S1). Since these AHR1 LBDs mostly belong to North American species, we additionally sequenced 14 Far-East avian AHR1s in this study. The sequencing method for the Far-East species was described in the supporting information. In order to compare the AHR1 amino acid sequences from individual species, we conducted CLUSTALW alignment. Pairwise alignments were made to evaluate the amino acid identities among AHR1s using Mac Vector 7.1.
Phylogenetic analysis
To clarify the evolutionary relationship of AHR1 from each species, we conducted a phylogenetic analysis of AHR1 LBD nucleotide sequences using BEAUti and BEAST 1.7 (Bayesian evolutionary analysis sampling trees)46. To understand the distribution pattern of avian AHR1 LBD genotypes in the evolutionary classification of birds, we cited the latest avian phylogenetic tree provided by Prum et al.23 and highlighted the AHR1 genotypes in the tree.
Data collection of ecological factors affecting 113 avian species
The data on the ecological factors of each avian species were compiled from “Birds of Korea”47 and “All about birds” from the lab of Ornithology at Cornell University. The collected data were categorized as one of four ecological factors: habitat, food, nesting, and migration type (Table S2). We followed the criteria of IUCN red list classification schemes to classify the habitat (http://www.iucnredlist.org/). For the wetland category, we combined wetland, artificial aquatic, and marine intertidal areas, in accordance with the definition of wetland reported by Ramsar Convention Secretariat48, which includes marshes, peat lands, floodplains, rivers, lakes, and coastal areas. The avian diet was classified according to food sources that are the most representative in each species. The “aquatic arthropods” was defined as all aquatic organisms except fish and aquatic invertebrates, and an omnivorous diet as consisting of “terrestrial invertebrates and plants” for the species that consume insects in the breeding season and feed on plant-derived materials thereafter. Regarding migration types, we added “occasional migration” as the type of migration for the species that demonstrate a mix of behaviors, including residence and short-distance migration. In addition, we defined types of nesting related to tree according to the differences in the behavioral ecology of nesting for precise analysis of ecological factors: (1) tree nesting type, which builds nests on the branch, (2) tree cavity type, which uses the cavity on the tree not constructed by birds, and (3) tree drilling type, which uses the cavity drilled by birds. Details concerning each ecological factor used for the analysis are listed in Table S2.
Measurement of responses of avian AHR1s to 1,3,7-TriBDD
To compare the response of avian AHR1 genotypes to a naturally occurring dioxin, 1,3,7-TriBDD, we conducted an in vitro luciferase reporter-gene assay using cDNA clones of Ile_Ser type, chicken AHR1 (ckAHR1), Ile_Ala type, black-footed albatross AHR1 (bfaAHR1) and Val_Ala type, common cormorant AHR1 (ccAHR1).
Plasmids
The firefly luciferase vector containing chicken CYP1A5 (ckCYP1A5) promoter region, pGL4-ckCYP1A5-6XRE was constructed in our previous study14. Renilla luciferase reporter vector (pGL4.74 [pRL/TK], Promega) was used as a transfection control. The expression vectors of ckAHR1, bfaAHR1, ccAHR1, and chicken ARNT1 (ckARNT1) were previously constructed by inserting the respective full-length cDNAs into pcDNA3.1 zeo (+) (Invitrogen)10,14,49. The total amount of transfected DNA per well was kept constant at 300 ng by the addition of pcDNA3.1/Zero (+) vector without insert.
Preparation of standard solutions of 1,3,7-TriBDD
A standard solution of 1,3,7-Tribromodibenzo-p-dioxin (1,3,7-TriBDD) dissolved in toluene was purchased from AccuStandard, Inc. (New Haven, CT, USA), and dimethyl sulfoxide (DMSO) was purchased from Sigma-Aldrich (St. Louis, MO). 1,3,7-TriBDD was concentrated under a stream of nitrogen to dryness and dissolved in hexane. DMSO was then added and mixed by a vortex. The hexane layer was dried by rotor evaporation and then by nitrogen flow, afterwards prepared in DMSO as stock solution. The stock solution of 1,3,7-TriBDD was diluted serially (0.012~120 nM) with DMSO for ligand treatment. The final concentration of DMSO was adjusted to 0.1%.
In vitro AHR transactivation assay
The African green monkey kidney COS-7 cells, which express a little endogenous AHR protein were maintained in Rosewell Park Memorial Institute (RPMI-1640) Medium (Hyclone) supplemented with 10% fetal bovine serum (Hyclone) at 37 °C and 5% CO2. Reporter gene assay experiment was performed following the method of Lee et al.21. Cells (6 × 104 per well) were seeded in 24 well plates (1.9 cm2/well). The amounts of transfected vectors were as follows; 5 ng of ckAHR1, ccAHR1, 50 ng of ckARNT1 expression vectors, 20 ng of pGL4-ckCYP1A5 and 5 ng of pGL4.74 control vectors. Transfections of vectors with Lipofectamine LTX (Invitrogen) were carried out 18 h after the seeding of cells. For each well, the plasmid DNAs were mixed with 1 μl of Lipofectamine LTX Transfection Reagent. The mixture was added to cells in serum-free Opti-MEM (Invitrogen). After 5 h incubation, cells were treated for 18 h with the solution of either 0.1% DMSO (control) or 1,3,7-TriBDD, which was diluted in charcoal/dextran-treated RPMI 1640 with 10% charcoal/dextran-treated FBS. The luciferase activity was determined with the Dual Luciferase Assay System (Promega). Final luminescence values were expressed as a ratio of firefly luciferase unit to Renilla luciferase (relative luciferase unit, RLU).
Statistical analysis
Statistical analysis for ecological factors
All data were coded using the presence or absence marking method according to the ecological factors identified for each species. The ecological factors that did not belong to the variables defined in the analysis, were coded as “absence”; e.g., the Chilean flamingo, which feeds on algae, and the gray catbird, which needs no nest because it uses brood parasitism as a reproductive behavior, were coded as “absence” for food and nesting types, respectively.
The distributions of ecological factors according to AHR1 genotypes were analyzed with the cross tabulation test to determine the relatedness between certain ecological factors and AHR1 genotypes. When a species belongs to multiple coding categories, the species was coded with all of them. We then conducted a two-way cluster analysis to explore the relationship between the AHR1 genotypes and ecological factors. The distance between data was calculated by using the Euclidean algorithm, and hierarchical clustering was performed by Ward’s method. We then carried out NMDS to explore the ecological factors that may have driven natural selection pressures on the AHR1 genotypes in the evolutionary process of avian species.
A two-way cluster analysis and NMDS was conducted using PC-ORD 5.31 (MjM software design) and the cross tabulation test was performed using SPSS 18.0 (SPSS, Chicago, IL, U.S.A).
Statistical analysis for in vitro AHR1-mediated responses to 1,3,7-TriBDD
Responses to each concentration of 1,3,7-TriBDD were obtained from at least three replicates in four independent experiments. The RLU values in all wells were normalized by the mean of RLU values in solvent control (DMSO) wells. All data were shown as mean ± standard deviation (SD). The lowest observed effect concentration (LOEC) and the fold change in luciferase induction were determined by ANOVA test using Bonferroni as post-hoc comparisons (p < 0.01). ANOVA test was performed by SPSS 18.0 (SPSS, Chicago, IL, USA).
Additional Information
How to cite this article: Hwang, J.-H. et al. Ecological factors drive natural selection pressure of avian aryl hydrocarbon receptor 1 genotypes. Sci. Rep. 6, 27526; doi: 10.1038/srep27526 (2016).
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Acknowledgements
Funding support was provided to E.-Y. Kim from the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2013R1A1A2A10010043, 2012K2A2A4021504). Financial assistance was also provided by National Institute of Environmental Research, Korea. This work was supported by Grants-in-Aid KAKENHI for Scientific Research (S) [No. 26220103], and Joint Research Project under the Japan-Korea Basic Scientific Cooperation Program for FY 2016, from Japan Society for the Promotion of Science (JSPS), which were given to Hisato Iwata. This study was also supported by the Ministry of Education, Culture, Sports, Science and Technology, Japan (MEXT) to a project on Joint Usage/Research Center – Leading Academia in Marine and Environmental Research (LaMer).
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J.-H.H. and E.-Y.K. designed experiments and wrote the manuscript text. J.-Y.P. provided the bird samples and their ecological information. H.I. and M.H. wrote the manuscript text and prepared Figure S3. H.-J.P. and S.-M.B. analyzed the AHR sequences and prepared Table 1, Figures S1, S2 and Figures 1, 2. Y.-S.P. conducted data analysis of ecological factors and prepared Figure 5. All authors reviewed the manuscript.
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Hwang, JH., Park, JY., Park, HJ. et al. Ecological factors drive natural selection pressure of avian aryl hydrocarbon receptor 1 genotypes. Sci Rep 6, 27526 (2016). https://doi.org/10.1038/srep27526
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DOI: https://doi.org/10.1038/srep27526
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