Volatiles of Symbiotic Bacterial Origin Explain Ectoparasitism and Fledging Success of Hoopoes

Mazorra‑Alonsoetal. Animal Microbiome (2024) 6:26 https://doi.org/10.1186/s42523‑024‑00312‑9 RESEARCH Volatiles ofsymbiotic bacterial origin explain ectoparasitism andfledging success ofhoopoes Mónica Mazorra‑Alonso1, Juan Manuel Peralta‑Sánchez2*, Manuel Martín‑Vivaldi3,5, Manuel Martínez‑Bueno4,5, Rafael Núñez Gómez6 and Juan José Soler1,5* Abstract Background Some parasites use olfactory cues to detect their hosts and, since bacterial symbionts are partially responsible for animal odours, they could influence host parasitism. By autoclaving nest materials of hoopoe (Upupa epops) nests before reproduction started, we explored the hypothetical links between host‑associated bacteria, vola‑ tiles and parasitism. During the nestling stage, we (i) estimated the level of ectoparasitism by chewing lice (Suborder Mallophaga) in adult hoopoe females and by Carnus haemapterus flies in nestlings, and (ii) characterized microbial communities and volatile profiles of nest environments (nest material and nest cavity, respectively) and uropygial secretions. Results Experimental nests had less diverse bacterial communities and more diverse volatile profiles than control nests, while occupants experienced lower intensity of parasitism in experimental than in control nests. The experi‑ ment also affected beta diversity of the microbial communities of nest material and of the volatiles of the nest‑ ling uropygial secretions. Moreover, microbial communities of uropygial secretions and of nest materials covaried with their volatile profiles, while the volatile profile of the bird secretions explained nest volatile profile. Finally, a subset of the volatiles and bacteria detected in the nest material and uropygial secretions were associated with the ectoparasitism intensity of both adult females and nestlings, and with fledging success. Conclusions These results show that a component of animal odours is linked with the microbial communities of the host and its reproductive environment, and emphasize that the associations between bacteria, ectoparasitism and reproductive success are partially mediated by volatiles of bacterial origin. Future work should focus on mecha‑ nisms underlying the detected patterns. Keywords Animal odour, Avian microbiota, Carnus hemapterus, Eavesdropping parasites, Fermentation hypothesis, Uropygial secretion Open Access © The Author(s) 2024. 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Animal Microbiome *Correspondence: Juan Manuel Peralta‑Sánchez [email protected] Juan José Soler [email protected] 1 Departamento de Ecología Funcional y Evolutiva, Estación Experimental de Zonas Áridas (CSIC), Almería, Spain 2 Departamento de Zoología, Universidad de Sevilla, Seville, Spain 3 Departamento de Zoología, Universidad de Granada, Granada, Spain 4 Departamento de Microbiología, Universidad de Granada, Granada, Spain 5 Unidad Asociada (CSIC): Coevolución: Cucos, Hospedadores y Bacterias Simbiontes. Universidad de Granada, Granada, Spain 6 Servicio de Instrumentación Científica, Estación Experimental del Zaidín (CSIC), Granada, Spain Page 2 of 24 Mazorra‑Alonsoetal. Animal Microbiome (2024) 6:26 Background Symbiotic microorganisms are essential for understanding the evolution and functioning of their animal hosts [1–4]. For instance, bacterial symbionts are partly responsible for the emission of volatiles that contribute to animal odours [1, 5], and then these microorganisms may play key roles in animal communication [6–9]. The possible role of bacteria contributing to animal odours and informing on animal characteristics was first posited within the fermentation hypothesis [10, 11]. This hypothesis was initially restricted to odours derived from mammalian secretions used in chemical communication, but it is currently extended to secretions of other animal taxa [6, 7]. Exocrine glands that open out of the body greatly determine their volatile profile (i.e. odour) of animals [12–17] and, since glands provide suitable environments for bacterial growth [8, 18–21], odour profile could be partially produced by bacteria that inhabit those glands. The only exocrine gland birds have in the skin is the uropygium [22, 23], which produces secretion rich in volatiles [24] that, at least partially, could be by-products of the metabolism of bacterial symbionts [25]. In accordance, hoopoes (Upupa epops) [25] and dark-eyed juncos (Junco hyemalis) [26] host bacteria in their uropygial glands that produce key volatiles that are apparently involved in chemical social communication [8, 26, 28, but see 29]. Therefore, a relationship between diversity and composition of bacterial communities and volatile profiles of the uropygial secretion is therefore a key prediction of the hypothesized role of bacteria in animal odours. Evidences supporting this prediction has been found in different taxa, including mammals [19, 21], insects [5, 30–32] and amphibians [33]. In birds, the role of microorganisms mediating the odours of avian nests or uropygial secretions is a rapidly growing field of research [28, 29, 34, 35]. The hypothetical informative value of volatiles of bacterial origin implies that they might be involved in animal communication, either as signals [sensu 36], or as Inadvertent Social Information [ISI, sensu 37] that would be of interest for con- and hetero-specifics [7]. Communities of symbiotic bacteria, including the gut microbiota, are usually related to phenotypic condition, immune-state, physiology and behaviour of their animal hosts [3]. Then, particularities of the volatile profiles of bacterial origin would inform on these or other host traits. Accordingly, particular volatiles of bacterial origin are related to host sex, age, social status, or even group membership of individuals in some taxa [19, 27, 28, 38], which is valuable information for interacting conspecifics. In addition, hetero-specifics ectoparasites and predators frequently use animal odours as cues to detect or select their hosts [39–43]; some of those odours are possibly produced by bacterial symbionts [1, 2, 7, 9]. In accordance with this scenario, the experimental modification of the microbiota of nest materials affects the volatile profiles of great tit (Parus major) nests [44], the intensity of Carnus hemapterus ecto-parasitism suffered by hoopoe nestlings [45], and the probability of nest predation experienced by spotless starling (Sturnus unicolor) nestlings [46]. Volatiles of symbiotic bacterial origin might also act as repellent of ectoparasites and predators, indicating that their effects on host-parasite interactions are complex [47]. For instance, depending on the considered skin bacteria of humans and their produced volatiles, they can attract or repel mosquitoes [48, 49]. This scenario leads to the hypothesis that volatiles produced by bacterial communities are partially determining the intensity of parasitism and/or the probability of predation of their animal hosts. Therefore, host traits favouring bacterial symbionts that reduce the strength of selection pressures imposed by predators and parasites on their hosts would be adaptive [50]. The hoopoe is one of the few species where a link between the complex symbiotic bacterial community present in their uropygial gland [51–53] and the volatile components of their secretion has been experimentally demonstrated [25]. Moreover, hoopoes do not build nests, but prefer to re-use nest cavities with soft-material remains from previous reproductive events of conspecifics or heterospecifics [54]. The mutualistic association between hoopoes and the antibiotic-producing bacteria of their uropygial gland only appears during the nesting phase (i.e. within nest cavities) [55], and nest material from previous reproduction affects the bacterial community of the uropygial gland [54]. Finally, autoclaving the old-nest material before reproduction affects both the density of bacteria in hoopoe nests and the intensity of ectoparasitism suffered by nestlings [45]. However, current knowledge lacks for evidences supporting the expected link between the effects of volatiles produced by microbial symbionts and risk of parasitism in nesting birds, including hoopoes. The hypothetical role of chemicals of bacterial origin determining parasitism in hoopoes assumes that bacterial communities and volatiles profiles of particular environments should be related to each other. Then, we first explore whether particularities of the microbiota of the nest environment (i.e., nest material and uropygial secretion of females and nestlings) associated with volatile profiles of the nest environment and of the uropygial secretions of adult females and nestlings. Moreover, we also explore whether volatiles of the nest environment and those of the uropygial secretion of nesting birds (adult females and nestlings) associated to each other, which will shed light on the hypothetical contribution Page 3 of 24 Mazorra‑Alonsoetal. Animal Microbiome (2024) 6:26 of animal secretion volatiles on the general odour of nest environment that parasites might use to detect host nests. Adult females rarely leave the nest during the incubation and hatching periods (8–10days after the first egg hatches) [56], while the preen gland of nestlings usually starts to produce secretion on the sixth to seventh day after hatching [55]. Thus, we tested those assumptions with samples collected from hoopoe nests, females and nestlings at the beginning of the nestling period, and from hoopoe nests and nestlings at the end of the nestling stage. Taking advantages of current knowledge in hoopoes, we hypothesized that volatiles produced by bacterial communities are, at least partially, determining the intensity of parasitism of their host. For this purpose, we experimentally manipulated the bacterial environment of hoopoe nests by installing new nest-boxes added with old nest material that were (experimental) or were not (control) previously autoclaved. We explored the experimental effects on bacterial communities and volatile profiles of nest material and uropygial secretion of adult females and nestlings. We estimated intensity of parasitism of nestling and adult females by the hematophagous fly C. hemapterus and by chewing lice, respectively. C. hemapterus is the most abundant ectoparasite of hoopoe nestlings in our study area [51, 66], while chewing lice (Suborder Mallophaga) are frequently detected in adult nesting females, but not in nestlings. As C. hemapterus likely use odours to search and locate active nests [57], and its parasitism likely affect fledging success [58], we explored the association between diversity of the bacterial communities and of the volatile profiles of the nest environments and ectoparasitism and fledging success of hoopoes. Results Bacteria andvolatiles fromnest material anduropygial secretions The sequencing of the bacterial community of nest material produced 11,566,822 sequences and 2,481,899 were retained in the ASV table after filtering (number of samples = 144, average number of sequences per sample (min, max) = 17,235.41 (5000, 51,256)). The sequencing of uropygial secretion samples produced 17,866,248 sequences and 10,755,653 were retained in the ASV table after filtering (number of samples = 344, mean average number of sequences per sample (min, max) = 31,266.43 (8,723, 64,867)). The number of collected bacterial samples from experimental, control and natural nests is listed in the Additional file1: TableS1. 153 ASVs were retained in nest material samples and 50 ASVs in uropygial secretion samples for subsequent analyses. At the phylum level, nest material was dominated by Proteobacteria, followed by Firmicutes, Bacteroidetes and Actinobacteria at both nestling stages (Fig.1A). At the genus level, Psychrobacter resulted the most dominant bacteria genus in nest samples, although minority ASVs were abundant (between 18 and 31%, Fig.1B). Firmicutes were the phylum with the highest relative abundance in secretion samples, followed by Bacteroidetes and Actinobacteria (Fig.1C). Accordingly, Clostridium and other genera belonging to Order Clostridiales presented the highest relative abundances in these samples (Fig.1D). Acetic and butanoic acid and benzaldehyde were the most abundant volatiles in all samples (Fig.2), and the relative abundance of the rest of volatiles depended of the type of sample. Some aldehydes as hexanal, heptanal and nonanal resulted relatively more abundant in nest samples, while isocaproic, propionic and isovaleric acids and phenol were relatively more abundant in secretion samples of females and nestlings (Fig.2). Effects ofautoclaving nest material inbacterial communities andvolatile profiles ofthenest environment After controlling for the effect of laying date and study year, bacterial communities of nest material at the beginning (Shannon Index: F = 5.73, d.f. = 1,63, P = 0.020; Faith’s PD Index: F = 18.0, d.f. = 1,63, P < 0.001; Fig.3) and at the end of the nestling stage (Shannon Index: F = 2.39, d.f. = 1,50, P = 0.129; Faith’s PD Index: F = 5.19, d.f. = 1,50, P = 0.027; Fig.3) showed lower alpha diversity in experimental than in control nests (Additional file1: TableS2). Both communities separated to each other (i.e., beta diversity) at the beginning, and at the end of the nestling period (for Aitchison and PhilR distance matrixes) (Table1; Fig.4). Nest materials of unmanipulated nest-boxes (i.e., natural nests) showed bacterial communities of lower alpha (See figure on next page.) Fig. 1 Microbial composition at the phylum and the genus levels of nest materials (A and B), and of adult female and nestling secretions (C and D) collapsed by experimental treatment at different nestling periods (1: 6–8 days old nestlings; 2: 17 days‑old nestlings). While in experimental nest, nest material was autoclaved before the reproduction started and placed in new nest boxes, in control ones, the nest material was not autoclaved and placed in new nest boxes. In natural nests, old nest boxes and nest material were not manipulated. Taxa in the legend are sorted from the most to lowest abundant Page 4 of 24 Mazorra‑Alonsoetal. Animal Microbiome (2024) 6:26 Fig. 1 (See legend on previous page.) Page 5 of 24 Mazorra‑Alonsoetal. Animal Microbiome (2024) 6:26 Fig. 2 Volatile profile of nest materials and of adult female and nestling secretions collapse by experimental treatment at different nestling periods (1: 6–8 days old nestlings; 2: 17 days‑old nestlings). While in experimental nest, nest material was autoclaved before the reproduction started and placed in new nest boxes, in control ones, the nest material was not autoclaved and placed in new nest boxes. In natural nests, old nest boxes and nest material were not manipulated Page 6 of 24 Mazorra‑Alonsoetal. Animal Microbiome (2024) 6:26 diversity than those of control nests (Additional file1: TableS3) both at the beginning (Shannon Index: F = 2.92, d.f. = 1,42, P = 0.095; Faith’s PD Index: F = 36.0, d.f. = 1,42, P < 0.001) and at the end of the nestling stage (Shannon Index: F = 7.49, d.f. = 1,50, P = 0.010; Faith’s PD Index: F = 6.03, d.f. = 1,50, P = 0.020). Those bacterial communities also differed in terms of beta-diversity indexes (PERMANOVAs: early stage: Pseudo F > 3.85, d.f. = 1,42, P < 0.001; late stage: Pseudo F > 4.53; d.f. = 1,33, P < 0.001). At the beginning of the nestling stage, Staphylococcus spp. was more abundant in nest materials of control nests than in those of experimental nests. Staphylococcus spp., Nocardia spp., Yaniella spp. and an unknown genus belonging to the Order Lactobacillales were more abundant in control nests than in unmanipulated nests (ANCOM analyses, Table2). At the end of the nestling period, the genera Corynebacterium spp. was more abundant in the material collected from control than experimental nests. Yaniella spp. was more abundant in materials of control nests than in those from unmanipulated nests (ANCOM analyses, Table2). Fig. 3 Alpha diversity of the bacterial communities (Shannon and Faith’s phylogenetic diversity (PD) indexes) and of volatile profiles (Shannon index) of samples collected in experimental (old nest material from previous reproduction was autoclaved and used to fill new nest boxes before reproduction started) and control nests (old nest material from previous reproduction was directly used to fill new nest boxes). Analysed samples included volatiles from nest environment (days four and 15 after hatching), and from female (Day 4 after hatching) and nestling (days 8 and 19 after hatching) uropygial secretions, and bacterial communities from the nest material (days four and 15 after hatching) and from the secretion of females and nestlings. Values are means ± 95% CI Page 7 of 24 Mazorra‑Alonsoetal. Animal Microbiome (2024) 6:26 Volatile profiles of nest environment, at the early nestling stage, were significantly more diverse in experimental than in control nests (alpha diversity, GLM: F = 5.43, d.f. = 1,55, P = 0.023; Fig.3 ALPHA), after controlling for the significant effects of study year and laying date (Additional file1: TableS2). However, at that nestling stage, beta diversity of volatiles did not differ between experimental treatments (Table1; Fig.4). No differences in alpha or beta diversity was found at the end of the nestling stage (Additional file1: TableS2; Fig.3; beta diversity: Table1, Fig.4). Similarly, when comparing volatile profiles of control and natural nests, statistical significant differences were not detected, independently of the sampling period (alpha diversity, early stage GLM: F = 1.51, d.f. = 1,28, P = 0.230; late-stage GLM: F = 0.27, d.f. = 1,26, P = 0.607; beta diversity, early stage PERMANOVAs: Pseudo F < 0.60, d.f. = 1,28, P > 0.750; late-stage PER- MANOVAs for nestlings: Pseudo F < 0.60, d.f. = 1,26, P > 0.720). Finally, the abundances of none of the detected volatiles differ significantly (P > 0.05) between treatments (ANCOM analyses, results no shown). Effects ofautoclaving nest material inbacterial communities andvolatile profiles oftheuropygial gland secretions ofnestlings andadult females Autoclaving nest material before reproduction started did not induce changes on the microbiota of the uropygial secretion of nestlings or adult females. After taking into account the effects of study year and nestling stage, our experiment did not affect alpha (Shannon or Faith’s PD; F1,74 < 0.02, p > 0.896; Fig.3; Additional file1: TableS2) or beta diversity (Table1), or the abundance of any of the detected bacterial genera (ANCOM analyses, Table2) in the uropygial secretion of adult females. Similarly, the experiment neither affected alpha (Shannon or Faith’s PD, F1,61 < 0.53, p > 0.470; Additional file1: TableS2) nor beta diversity of the bacterial community of the uropygial secretion of nestlings (Fig.3; Table 1 Results from PERMANOVAs exploring the effects of the experimental sterilization of nest materials before reproduction on beta‑diversity indexes of bacterial communities (Aitchison and PhilR) and volatile profiles (Aitchison) of different sample types collected at different nestling ages (day) The models included study year (2017 vs. 2018) and laying date (early vs. late reproduction) as fixed factors. P values lower than 0.05 are in bold font Experimental treatment Study year Laying date Pseudo F df p Pseudo F df p Pseudo F df p Bacterial communities Nest material (day 4) Aitchison 4.59 1,57 < 0.001 2.41 1,57 0.002 1.28 1,57 0.149 PhilR 3.47 1,57 0.003 6.02 1,57 < 0.001 1.23 1,57 0.240 Nest material (day 15) Aitchison 3.76 1,50 0.001 3.52 1,50 < 0.001 1.40 1,50 0.118 PhilR 4.49 1,50 0.001 7.54 1,50 < 0.001 1.55 1,50 0.122 Female secretion (day 4) Aitchison 1.24 1,74 0.173 1.00 1,74 0.458 1.18 1,74 0.230 PhilR 0.84 1,74 0.480 0.83 1,74 0.534 0.39 1,74 0.990 Nestling secretion (day 19) Aitchison 1.03 1,61 0.410 1.31 1,61 0.111 0.95 1,61 0.547 PhilR 0.57 1,61 0.753 0.67 1,61 0.643 2.44 1,61 0.045 Volatile profiles Nest box (day 7) Aitchison 1.54 1,55 0.129 23.68 1,55 < 0.001 5.34 1,55 < 0.001 Nest box (day 18) Aitchison 0.49 1,51 0.868 12.12 1,51 < 0.001 3.39 1,51 0.004 Female secretion (day 4) Aitchison 0.57 1,80 0.671 7.92 1,80 < 0.001 0.73 1,80 0.548 Nestling secretion (day 8) Aitchison 1.94 1,63 0.085 11.99 1,63 < 0.001 1.19 1,63 0.282 Nestling secretion (day 19) Aitchison 1.12 1,63 0.319 15.05 1,63 < 0.001 2.50 1,63 0.041 Page 8 of 24 Mazorra‑Alonsoetal. Animal Microbiome (2024) 6:26 Table1). Finally, the relative abundance of Lactococcus spp. was higher in experimental nests than control in control ones (ANCOM analyses, W = 199, experimental relative abundance = 3202, control ones = 1004). Bacterial community of the uropygial gland secretion of adult females and nestlings from control and natural nests did not differ in terms of alpha (Shannon or Faith’s PD; adult females: F < 2.55, df = 1,53, P > 0.116; nestlings: F < 0.10, df = 1,39, P > 0.579; Additional file1: TableS3) or beta diversity (PERMANOVAs for adult females: Pseudo F < 1.26, d.f. = 1,53, p > 0.167; PER- MANOVAs for nestlings: Pseudo F < 1.30; d.f. = 1,39, p > 0.132). Only the relative abundance of Propionibacterium spp. was significantly higher in the female secretion of experimental nest than in female secretion of unmanipulated nests (ANCOM analyses, W = 30, experimental relative abundance = 290, unmanipulated ones = 8). With respect to volatile profiles, estimated alpha and beta diversity of volatile profiles of the uropygial secretions of adult females or nestlings did not differ between experimental and control nests (Table1; Additional file1: TableS2). Similarly, volatile profiles of the uropygial secretion of adult females or nestlings from control and natural nests did not significantly differ in terms of alpha (Additional file1: TableS3) or beta diversity (PERMANOVAs: Pseudo F < 1.97, d.f. = 1,50, p > 0.087). However, abundance of some of the detected volatiles in adult female secretions differed significantly between experimental, control and natural nests (ANCOM analyses, Table3). Associations betweencomposition ofthebacterial communities andthevolatile profiles Bacterial communities of the uropygial gland secretion of adult females (Mantel tests, R2 < 0.01, p = 0.771) or nestlings (Mantel tests, R2 < 0.01, p = 0.606) did not predict their respective volatile profiles. In spite of bacterial profiles of nest material at the beginning of the nestling period did not predict volatile profiles of nest environment (Mantel tests, R2 < 0.001, p = 0.317), bacterial profiles of nest material at the end of the nestling Fig. 4 Principal coordinate analyses of the bacterial communities of experimental (red) and control (blue) nest materials of hoopoe nest‑boxes. Samples collected at the beginning of the nestling stage were based in Aitchison (A) and PhilR distance (B). Similarly, samples collected at the end of the nestling stage were based in Aitchison (C) and PhilR distance (D). (B and D) Page 9 of 24 Mazorra‑Alonsoetal. Animal Microbiome (2024) 6:26 stage was correlated with its volatile profile (Mantel tests, R2 = 0.012, p = 0.037). Relative abundance of particular bacterial taxa and volatiles from the uropygial secretion of adult females and nestlings summarized in PC factors (hereafter PC, Additional file2: Tables S4 and S5, respectively) resulted related to each other. In adult females, volatile PC1, PC2 and PC4 were related with bacterial PC5, PC2, and PC3, respectively (Fig.5; Additional file1: TableS6). In nestlings, at the late stage of their nesting period, volatile PC2 correlated significantly with bacterial PC3, while volatile PC3 associated significantly with bacterial PC2 and PC3 (Fig.5; Additional file1: TableS6). At the beginning of the nestling stage, only bacterial of nest material PC6 explained significantly volatile PC1 of the nest environment (Fig.5; Additional file1: TableS6). At the end of the nestling stage, volatiles PC2 and PC4 of the nest environment associated with bacterial PC2 and PC5, respectively (Fig.5; Additional file1: TableS6). Associations betweenvolatile profiles ofnest environments andofsecretions At the beginning of the nestling stage, volatile profiles of the uropygial secretion of nestlings (Mantel tests, R2 < 0.017, p = 0.047) but not that of adult females (Mantel tests, R2 = 0.004, p = 0.134) explained the volatile profiles of nest environment. Different volatiles of adult females and nestling secretions associated with the volatile profile of the nest environment (Additional file1: TableS8). At the beginning of the nestling period, relative abundance of volatiles from female secretion summarized by PC1 and PC2, and by PC1, PC2 and PC3) respectively associated with relative Table 2 Pairwise differences in abundance of particular bacterial genus between experimental (E) and control (C) nests, and between each of them and unmanipulated (N‑natural) nests Statistical tests were separately performed for each bacterial community. For statistically significant comparisons, we show W values from ANCOM analyses, and mean abundance of bacterial genera in each compared group ( X s). Only bacterial taxa for which we found statistically significant differences are shown Nest material (day 4) Nest material (day 15) E–C W X sE–N W X sC–N W X sE–C W X sE–N W X sC–N W X s Staphylococcus spp. 418 992–6425 –442 6425–200 – – – Nocardia spp. –439 2474–191 – – – Unidentified genus of the order Lactobacillales –421 989–141 – – – Yaniella spp. –410 936–69 – – 316 344–88 Corynebacterium spp. – – 252 851–652 – – Unidentified genus of the family Sphingonomadaceae –397 96–403 -– – – Sphingobium spp. –384 177–547 – – – – Unidentified genus of the order Sphingonomadales –383 187–506 –– – – Sphingomonas spp. – – – – 283 48–569 – Dyadobacters spp. –339 189–800 –– – – Table 3 Pairwise differences in relative abundance of chemical volatiles between females in experimental (E) and control (C) nests, and between each of them and natural (N) nests, in female secretions For statistically significant comparisons, we show W values from ANCOM analyses, and mean relative abundance of volatiles in each compared group ( X s). Only volatiles for which between‑groups comparisons reached statistical significance are shown Female secretion (day 4) E–C W X sE–N W X sC–N W X s Esters Nonanoic acid methyl ester – 15 1.07–1.64 5 1.09–1.64 Heptanoic acid mehyl ester – 13 1.51–1.36 2 1.10–1.36 Butanoic acid ethil ester – 1 1.26–1.00 Acids Nonanoic acid – 5 1.04–1.18 Butanoic acid – 4 12.38–9.16 Pentanoic acid – 4 1.76–1.42 Isobutyric acid – 2 2.58–1.90 Octanoic acid – 2 1.04–1.29 Acetic acid – 1 13.88–12.40 Isocaproic acid – 1 10.99–4.96 Page 16 of 24 Mazorra‑Alonsoetal. Animal Microbiome (2024) 6:26 The detected associations are in any case complex and our results strongly support a central role of volatiles of symbiotic bacterial origin. However, the importance of different bacterial taxa and of different volatile compounds determining risk of parasitism and fledging success urges further experimental approaches. These associations between some groups of bacteria and volatiles of different types of samples associated with fledging success indicating that these chemical and microbiological components may influence host fitness. Material andmethods Study area andspecies The study area was located in the Hoya de Guadix, (Granada, Southern Spain, 37°18′N, 38°11′W), a plateau at 1000m a.s.l. with semiarid climate, where around 300 cork-made nest-boxes were available for wild birds; most of them attached to tree trunks and walls, but also hidden in piled stones. The dimensions of nest-boxes were 35 × 18 × 21cm (internal height × width × depth), 24cm (bottom-to-hole height) and 5.5cm (entrance diameter). Information about the study area is further described elsewhere [54, 68]. The hoopoe (Order Upupiformes) is a migratory species, distributed throughout Europe, Asia, and Africa [69–71]. Hoopoes are hole-nesters that frequently use artificial nest-boxes for reproduction or natural cavities in trees or walls. They do not build nests and prefer cavities with remains of soft material from previous reproductive events of conspecifics or heterospecifics [54], where adult females create a small hollow and lay the clutch [56]. In our study area, the reproductive season starts in late February, and extends until late July. C. hemapterus, a common generalist hematophagous parasitic fly of about 2 mm in length [57, 72] usually cause bleeding at the sucking spots. In hoopoes, chewing lice are common on the feathers of the crest where they are more protected from bird preening, as birds can only reach this area with their feet. Chewing lice feed by chewing soft areas of the feathers and skin of their avian hosts [73, 74]. Fieldwork andexperimental design Fieldwork and labwork, including autoclaving and sampling collection, were carried out during 2017 and 2018. Before reproduction started (i.e. beginning of February), we visited nest-boxes where hoopoes successfully bred the previous year. We collected old nest materials (47 nest-boxes in 2017 and 70 in 2018) in plastic bags perforated with small holes to maintain the nest material in aerobic conditions. Nest materials were stored at room temperature in the lab for three weeks until it was used to fill new installed nest-boxes. Hence, nest materials from different nest-boxes were pooled, mixed, and divided in two halves. C. hemapterus flies pupate overwinter inside bird nests, and autoclaving the nest material should kill them. Therefore, after treatment, experimental and control material could differ not only in bacterial density but also in the probability of C. hemapterus flies emerging within the control nest boxes, which might affect experimental outcomes. To evaluate this potential bias, we removed in 2018 all pupae from the material of both experimental treatments before autoclaving. We did so by sifting nest-material with opening meshes of 2, 1, and 0.5cm diameters. Interestingly, it was in that year when the expected effect of experimental autoclaving nest material on intensity of parasitism was clearer [45]. Moreover, to avoid any possible influence of previous reproduction on bacteria communities and volatile profiles, we installed new nest-boxes (86 in 2017 and 69 in 2018). Most of the times, new nest-boxes substituted old ones, although we placed also new nest-boxes in new locations in the field with any of the experimental levels. New nest-boxes were sequentially assigned to one of the two experimental treatments, adding 500 cm3 of nest material from previous reproduction, that were (experimental) or were not autoclaved (control), mixed with 500 cm3 of commercial sawdust (Allspan® Animal bedding, wood shavings). This procedure was performed by wearing new pair of latex gloves cleaned with 96% ethanol for each nest-box to avoid cross-contamination between experimental and control nests materials. The third group of nest-boxes (i.e., natural nests), old nest-boxes were neither new nor manipulated, and where hoopoes bred the year of sampling (N = 13 in 2017 and N = 14 in 2018). As bacteria and volatile environment likely depends on previous reproduction, we here only considered first breeding attempts. During reproduction, from early March to the end of June, both new (i.e., experimental and control) and old (i.e. natural) nest-boxes in the study area were visited every four days until eggs were found inside. Hoopoes lay one egg per day, and clutch size is typically of seven eggs, start incubation with the first or second egg and incubation last around 17days [75]. Then, the rate of nest visiting allowed us to estimate laying date (i.e. that of the first egg). Nest-boxes where inspected again 17days after the onset of egg laying, and daily afterwards until detecting hatching date (day 1 of the nestling period), which is expected to occur 17days after the onset of incubation [75]. During the nestling stage, nests were visited seven times (details below and Additional file1: TableS1) to sample nest materials, volatiles Page 17 of 24 Mazorra‑Alonsoetal. Animal Microbiome (2024) 6:26 of the nest environment and uropygial secretions, as well as to record parasitism intensity of adult females and nestlings (Additional file1: TableS1). For collecting each of these samples within a nest, we wore new pair of latex gloves previously cleaned with 96% ethanol to avoid contamination between samples. Multiple visits were needed to ensure that disturbances to the nests due to the time required to collect samples were not unduly long (i.e. multiple visits needed to minimize negative impacts of researcher visits that could have biased breeding success). Bacterial, volatile andectoparasite sampling For bacterial community analyses, approximately 10 g of the nest material in contact with nestlings was collected twice in 15mL Falcon tubes, on days 4 and 15 after the first egg hatched (Additional file1: TableS1). These samples were stored in a portable fridge until being frozen at –20°C in the laboratory within the same day of collection. Volatile compounds of the nest environment were also sampled twice, on days 7 and 18 after the first egg hatched (Additional file1: TableS1). Volatiles were captured in Solid Phase Microextraction (SPME) fibres. Each fibre was installed at one side of the nest-box, about 7cm over the nest material, while the sensitive fibre end was protected with a two-side opened glass pipette tip and exposed to the nest environment for 24h. Afterwards, the fibre was removed from the nest and the fibre end introduced into a sealed glass vial, kept cold (0–4°C), and stored within the same day at –20°C until gas chromatography–mass spectrometry analysis. Storage of samples never exceeded one week. After the analyses, SPME fibres were re-conditioned (i.e., all chemical trace eliminated) following supplier instructions, i.e. 1h at 270°C using the GC injector and afterwards, fibres were kept at –20°C until they were reused in the field. Uropygial secretions were collected on days 4 (adult females), 8 and 19 (nestlings) after the first egg hatched (Additional file1: TableS1). Briefly, before sampling, the uropygial gland and surroundings were cleaned with a cotton swab soaked in 96% ethanol. Afterwards, we used an automatic 1–10 μL micropipette and gently introduced the sterilized tip into the papilla of the uropygial gland and pipetted the secretion. At least 5μL of secretion from adult females or close-to-fledge nestlings was placed in a sterile 1.5mL microcentrifuge tube for bacterial DNA analyses. In addition, 10 μL were transferred to 10ml SPME sealed glass vials for analyses of the volatile profile. Six to eight days old nestlings produce scarce uropygial secretion, so these secretions were employed only for exploring volatile profiles of nestlings. Since we were interested on the chemical profile of nests, we sampled a single nestling per nest (usually the largest one) at this nestling stage, and, when not reaching 10 μL volume, we completed with the secretion of other siblings. At the end of the nestling stage, we sampled all nestlings in the nest: Following same philosophy, we collapsed volatile and bacterial community data by nest (see below). Samples were kept cold in a portable fridge and then stored at –20°C within a week for chemical volatile analyses or until DNA extraction. Ectoparasitism of adult females was estimated on day 4 after the first egg hatched by counting the number of chewing lice on the crest feathers, which is a good proxy of parasitism intensity [73, 74]. Ectoparasitism of nestlings was estimated twice, when the older nestling was 8 and 19 days old (Additional file 1: TableS1). These estimates consisted of counting the number of spots due to faeces and blood remains on the belly skin and left underwing of all nestlings. These spots are traces of C. hemapterus parasitism and reflect the abundance of ectoparasites and, thus, the intensity of parasitism of nestlings [76, 77]. We used mean values per nest in the analyses. Finally, fledging success was estimated as the percentage of nestlings that survived from day 8 after hatching of the first egg until day 19. DNA extraction andhigh-throughput sequencing Bacterial DNA from secretions and nest material were extracted using the FavorPrep Blood Genomic DNA Extraction Kit (Favorgen Biotech) and MSOP protocol [78], respectively. For secretions, and according to manufacturer’s instructions, we added a lysozyme pretreatment (10mg/mL of lysozyme at 37°C for 30min) to ensure the DNA extraction of Gram positive bacteria [53]. Nest material samples were solid and 80mg were used for DNA extraction. First, samples were suspended with 900 µL of lysis buffer. The liquid phase was then separated from the solid content and kept in different 2mL microfuge tubes (for further details of the followed protocol see Lee etal. 2021). Extracted DNA from nest material samples was cleaned using the kit One Step PCR Inhibitor Removal Kit (Zymo Research). We also processed laboratory blanks to detect possible contamination during the process. DNA sequences from nest materials and uropygial secretions were obtained by Illumina high-throughput sequencing of a fragment of approximately 400bp of the 16S rRNA V6-V8 hypervariable regions. In a first PCR, 16S rRNA gene were amplified using universal primers B969F (5′-ACG GGC RGT GWG TRCAA-3′) and BA1406R (5′-ACG GGC RGT GWG TRCAA-3′) [79]. PCR was carried out at final volume of 25µL containing 12.5µL of iProof High-Fidelity DNA Polymerase (Bio- Rad Laboratories, Inc.), 0.3µM of each primer, and 5µL Page 18 of 24 Mazorra‑Alonsoetal. Animal Microbiome (2024) 6:26 of template DNA. PCR conditions included an initial denaturing step of 98 C for 1min followed by an amplification step of 25 cycles of 10s at 98 C, 20s at 52 C, and 15s at 72 C, and a final extension of 5min at 72 C. In a second PCR, samples were amplified adding barcodes for identifying samples. PCR was carried out at final volume of 25µL containing 12.5µL of iProof High-Fidelity DNA Polymerase (Bio-Rad Laboratories, Inc.), 0.3µM of each primer, and 5 µL of template DNA. PCR conditions included an initial denaturing step of 98 C for 1min followed by an amplification step of 25 cycles of 10s at 98 C, 20s at 52 C, and 15s at 72 C, and a final extension of 5min at 72 C. Afterwards, the libraries were sequenced in a single run of Illumina MiSeq sequencer (2 × 300bp output mode). Sequencing was carried out at the Integrated Microbiome Resource (IMR), University of Dalhousie (Canada). Sequences are available at NCBI under accession numbers: BioProyect ID: PRJNA847390 (nest samples) and BioProyect ID: PRJNA847428 (secretion samples). Raw sequences were analysed using QIIME2 2019.10 [80]. Briefly, primers were trimmed and, due to low quality of the reverse sequences, analyses were based on forward sequences. Sequences were quality filtered following default parameters in QIIME2 and the Deblur algorithm was employed to produce an Amplicon Sequence Variants table (ASV table) [81], with a sequence size of 220bp. Afterwards, a phylogenetic tree was built using the fragment insertion algorithm (Janssen etal. 2018). Taxonomic assignation was performed against Greengenes13_8 database at 97% similarity [16, 82]. Chloroplast, mitochondria and non-phylum assigned ASVs were removed. Sequences with fewer than 0.1% of reads and fewer of 10% of samples were filtered out and samples with fewer of 5000 sequences were removed from the ASV tables following criteria of Grieves etal. [27, 34]. Since we were interested on the chemical profile and bacterial community of nests, we collapsed tables related with nestlings at the late nestling period by calculating average values of volatiles and ASV by nests using QIIME2. Due to zero counts could mask true zeros from too low counts for Illumina detection, we replaced those zero values using a Bayesian-multiplicative replacement to impute values for zero count sequences. For this purpose, we used the R package zCompositions [83]. Afterwards, we applied a centred log-ratio (clr) transformation to the ASV tables [84, 85]. Volatile profiles: gas chromatography-mass spectrometry (GC–MS) Analyses were performed on a gas chromatograph coupled to a mass spectrometer Varian 450GC 240MS with an automatic injector Combi Pal to SPME fibre (50/30μm DVB/CAR/PDMS, Stableflex 23Ga, Autosampler). Injector desorption was performed at 250°C for 10min in Split (20: 1) and helium flow at 2mL/min. The capillary column was Aligent HP-FFAP 30m × 0.32mm × 0.25μm. The oven temperature was initiated at 50°C for 1min, and programmed to increase 5°C /min to 100°C, then at 10°C /min to 200°C and 50°C /min to 250°C for 1min. The scan range of the mass spectrometer was in mode TIC Full Scan between 30 and 500m/z. The identification of compounds was established by characteristic ion SIM analysis and the NIST 08 spectrum library (Fig.9). The summary of volatile profiles of next-box environments and uropygial gland secretions is in the Electronic Supplementary Material (Additional file 1: Table S7). Standards of pure compounds were used when necessary for confirmation. Volatile profiles were calculated as the relative abundance of each volatile in the chromatogram, i.e. the percentage of the area of each compound over the total area of the chromatogram adjusted to 100%. The number of volatile samples collected from experimental, control and natural nest-boxes is listed in Additional file1: TableS1. Statistical procedures Alpha diversity analyses (i.e. the microbial diversity within a particular sample) [86], of bacterial communities was estimated with the ASV table before zero replacement as by means of Shannon and Faith’s phylogenetic diversity (Faith’s PD) indexes in QIIME2 [80]. For beta diversity analyses (i.e., the variability in community composition among different samples) of bacterial samples [86], we calculated Aitchison distance, that calculates the Euclidean distance between pair of samples [87] and PhilR, which take into account the phylogenetic relationships among bacterial taxa [88]. For volatiles of the nest environment and uropygial gland secretions, we estimated alpha diversity using Shannon index, and beta diversity using the Aitchison distance between samples [87]. Alpha diversity indexes and Aitchison calculations were calculated using the default R package stats, while the philr package [88] was employed for the generation of the PhilR distance matrixes. This packages were implemented in R.3.6.1 [89]. General linear models (GLM) were performed to study the effect of experimental treatments on alpha diversity estimates. Distribution of alpha diversity values did not differ significantly from a Gaussian distribution (Kolmogorov–Smirnov test for continuous variables, P > 0.05). Full models included treatment and study year as fixed factors, laying date as covariable and interactions between treatments and study year. In case of interactions did not reach statistical significance, we run models without Page 19 of 24 Mazorra‑Alonsoetal. Animal Microbiome (2024) 6:26 these terms. Residuals of all GLMs approximately followed normal distributions. The effect of treatment on the beta diversity of bacterial communities and of volatile profiles were explored by means of PERMANOVAs (i.e., nonparametric multivariate analysis of variance) with 10 000 permutations. Full models included treatment and study year and early (end of March, April and first half of May) versus late (second half of May and June) reproduction as fixed factors and interactions between fixed factors. In case of interactions were not significant, we run models without these terms. These analyses were performed in PRIMER-7.0.17. To visualize segregation of bacterial communities and of volatile profiles due to experimental treatment, we Fig. 9 Example of SIM 60 m/z chromatograms of A) the nest environment of a hoopoe nest at the beginning of the nestling stage and of B) uropygial secretion of the brooding female. Peaks represent the acids detected in kcounts (from fewer carbons to higher carbons in the molecule: 1. acetic, 2. butanoic, 3. pentanoic, 4. hexanoic, 5. heptanoic, 6. octanoic, 7. nonanoic and 8. decanoic) Page 20 of 24 Mazorra‑Alonsoetal. Animal Microbiome (2024) 6:26 performed Principal Coordinates Analyses (PCoA) plots, implemented in Emperor 2018.2.0 [90]. Finally, we used Analyses of Composition of Microbiomes (ANCOM) [91], implemented in QIIME2, to determine which particular bacterial genus, or particular volatiles are responsible for the detected differences among experimental, control and natural nests. The associations between bacterial and volatile profiles of different types of samples were explored by mean of Mantel-test with 9999 permutations using the function MRM in the ecodist package [92] as implemented in R.3.6.1 [89]. That statistical test is equivalent to a multiple regression but using matrices of differences among samples in a multivariate setting. Importantly, given that for exploring the associations between bacterial and volatile profiles the matrices have to be estimated with the same methodology, we here calculated bacterial matrices based on Bray–Curtis dissimilarities. We selected the same samples in both matrices in QIIME2 before Mantel-test analyses to get the same dimensions in each analysis. To explore the associations between specific bacteria and specific volatiles of uropygial secretion and nest material samples, we used PC-scores (i.e., after varimax rotation) from Principal Component Analyses (PCA) of the clr-transformed relative abundances of the bacterial taxa (considering the first six axes) and of the clr-transformed relative abundance of the volatile components. Because the former PCA included more variable (i.e. taxa) than the later (chemical), the number of considered PC-axes in subsequent analyses were larger in those belonged to bacterial taxa (first six axes) than in PCAs of detected volatiles (four first axes). The associations between specific PC-scores describing relative abundance of particular volatiles (dependent variables) and those describing bacterial abundance (independent factors) were explored by mean of GLMs. Because we performed multiple GLMs (one per each PC-axis of volatiles), p-values describing the strength of the partial associations were adjusted for the effect of multiple testing [FDR, 93]. Similarly, we performed GLMs to explore the association between PC-scores describing relative abundance of volatiles of nests (dependent variable) and those of the uropygial secretion of adult females or nestlings (independent factors). In this case, associations were separately estimated for adult females and for nestlings, and, thus, we performed eight different GLMs. P-values were also adjusted following the FDR procedure [93]. PC- scores were also used to explore the associations between bacteria or volatiles components and intensity of parasitism or fledgling success. To search for the best combination of PC-axes describing bacterial communities and volatile profiles that explained the parasitism intensity of hoopoe nestlings and adult females, as well as fledging success, we used best subsets General Regression Models (GRM). The best subsets GRM was estimated by means of Mallow’s CP [94], which is equivalent to Akaike information criterion (AIC) [95]. Importantly, information on bacterial and chemical profiles were not always available for the same pool of nests, so we separately analysed the effect of chemical and bacterial information. Moreover, we did not successfully collect information for all types of samples within the same nest (e.g., nestling secretion, adult female secretion or nest material) and, thus, available sample sizes for models that included all types of samples were reduced. When none of the PC-axes describing bacterial (or volatiles) variation of one or more types of sample entered in the best model, we again ran the GRM but excluding these term from the list of independent factors. GRMs directed to identify best models explaining parasitism intensities estimated at different nest stage (i.e., early vs late nestling stage) included independent factors that summarize information on bacterial communities or volatiles profiles that were collected in appropriate nestling stage. In models that explores factors explaining parasitism of recently hatched hoopoe nestlings and in adult females, initial GRM included information on the bacterial communities or on volatile profiles of nests, nestling and adult female secretions that were collected at the beginning of the nestling period. Similarly, initial GRM explaining intensity of parasitism of nestlings close to fledging included information on bacterial communities and volatile profiles of material collected at the end of the nestling period (i.e., nest material and uropygial secretion of nestlings that were close to fledge). Finally, PC-factors accounting for bacterial and volatiles profiles of the secretions of females were used in the GRM analyses trying to explain chewing lice parasitism of adult females. We did so because we do not expect a major effect of bacteria or bacterial-derived volatiles from the nest or the nestlings on lice attraction in adult females, whose major mode of transfer is supposed to be through direct host contact [96]. GRM models were also used to search for factors explaining fledging success. To this aim, we performed two different GRMs that respectively considered information from samples collected during early or late nestling stages. Frequency distributions of square root transformed values of the intensity of ectoparasitism in nestlings, as well as raw values of fledging success did not differ significantly from Gaussian distribution (Kolmogorov– Smirnov test for continuous variables, p > 0.05). GLMs, GRMs and PCAs were performed in STATISTICA 12 software. Page 21 of 24 Mazorra‑Alonsoetal. Animal Microbiome (2024) 6:26 uropygial secretion of female and nestling hoopoes that explained para‑ sitism and fledging success. Values are PC factor loadings after varimax normalized rotated and in their nest material or nest boxes. Each PC‑axis was named by a composition of letters that indicate the type of samples. The first letter indicates whether the sample corresponds to bacteria (B) or volatiles (V), the second letter indicates whether the sample is from secretions of females (SF), nestlings (SN) or nest material (M). Finally, for types of samples that were collected at the beginning (1) and at the end (2) of the nestling period, the name finished with a number. Only factors than entered in final models explaining the intensity of ecto‑parasitism in females and nestlings and the fledging success are shown. N MAT refers to nest material and SECR to uropygial secretion. Additional file2.TableS4. Six first axes of Principal Component Analyses based on ASV table of bacterial community of different type of samples from hoopoes nests and secretions. TableS5. Six first axes of Principal Component Analyses based on volatile profile of different type of samples from hoopoes nests and secretions. Acknowledgements We thank Natalia Juárez García‑Pelayo and Cristina Ruiz Castellano for their help with the fieldwork, and Estefanía López Hernández and Miguel Rabelo Ruiz with the laboratory work. Gustavo Tomás read the manuscript and greatly improved its quality and understanding. We would like to acknowledge anonymous reviewers for their comments and suggestions that undoubtingly have improved the present manuscript. Author contributions MMV and JJS designed the study including the experimental approach. MMA, JJS and MMV carried out the fieldwork. MMA with the help of MMB performed all laboratory analyses related to bacterial DNA extraction and amplification. RNG afforded all chemical analyses in determination and quantification of chemicals. MMA and JMPS carried out all bioinformatics and statistical analy‑ ses. Together with JJS and JMPS, MMA wrote a first version of the manuscript. All authors contributed to the general discussion of results and to the final version of the manuscript. Funding Open Access funding provided thanks to the CRUE‑CSIC agreement with Springer Nature. The research group was supported by the projects CGL2017‑ 83103‑P, PID2020‑117429 GB‑C21 and PID2020‑117429 GB‑C22, funded by the Ministerio de Ciencia e Innovación/Agencia Estatal de Investigación/https:// doi.org/10.13039/501100011033and by “Fondo Europeo de Desarrollo Regional, a way of making Europe”. The research group also benefits from facil‑ ities, including accommodation, provided by the City Hall of Guadix, where a small lab to quickly process the samples was installed. JMPS enjoined a Ramon y Cajal scholarship (RYC2022‑036147‑I) funded by Ministerio de Ciencia, Inno‑ vación y Universidades (MCIN/AEI/https://doi.org/10.13039/501100011033). Data Availability Raw sequence reads and their metadata are deposited in the Sequence Read Archive (SRA) in the Genbank‑NCBI webpage (https:// www. ncbi. nlm. nih. gov/ sra/ ). Nest sequences are available under BioProject ID: PRJNA847390, acces‑ sion number, SUB11518282 and Secretion sequences under BioProject ID: PRJNA847428, accession number SUB11582000. Volatiles metadata are stored in DataDryad (https:// doi. org/ 10. 5061/ dryad. 8sf7m 0csn). Declarations Ethics approval and consent to participate The study was conducted according to relevant Spanish national (Decreto 105/2011, 19 de abril) and regional guidelines. All necessary permits for hoopoe´s manipulations were provided by Consejería de Medio Ambiente de la Junta de Andalucía, Spain (Ref: SGYB/FOA/AFR/CFS and SGMN/GyB/JMIF). Our study area is not protected, but privately owned, and the owners allowed us to work in their properties. The time spent in each hoopoe nest was the minimum necessary for the experiment. Supplementary Information The online version contains supplementary material available at https:// doi. org/ 10. 1186/ s42523‑ 024‑ 00312‑9. Additional file1.TableS1. Number of experimental (with autoclaved nest material), control (with non‑autoclaved nest material) and natural (with old nest material) hoopoe nests with information of bacterial com‑ munity, volatile profiles and parasitism at different nestling stages (day of sampling: days (d) after the first egg hatched). Bacterial and volatile samples were collected from the nest environment [nest material (Nest Mat) or nest air (Nest‑box) and from the uropygial gland (secretion) of females and nestlings. TableS2. General Lineal Models exploring the effect of autoclaving nest material on Shannon (Sh) and Faith’s phy‑ logenetic diversity (Pd) indexes of bacterial communities and volatile profiles at different nesting stages and nest locations. We show least square means (SE) for control and experimental (Exp) treatments, and for different study years, and beta (SE) values of the associations with laying date. Statistical effects lower than 0.05 are in bold. TableS3. General Lineal Models exploring the effect of using new nest boxes (i.e., Natural vs Control) on Shannon (Sh) and (Pd) alpha diversity indexes of bacterial communities and volatile profiles at different nesting stages and nest locations. We show least square means (SE) for control and experimental (Exp) treatments, and for different study years, and beta (SE) values of the associations with laying date. Statistical effects lower than 0.05 are in bold. TableS6. Multiple regression exploring the effect of the first six PC axes of the bacterial community on each of the first four PC axis of the volatile profile for the same type of sample. PC factor were calculated after varimax normalized rotation. Each PC‑axis was named by a composition of letters that indicate the type of samples. The first letter indicates whether the sample corresponds to bacteria (B) or volatiles (V), the second letter indicates whether the sample is from secretions of females (SF), nestlings (SN) or nest material (M). Finally, for types of samples that were collected at the beginning (1) and at the end (2) of the nestling period, the name finished with a number. TableS7. Results of PCA analyses summariz‑ ing bacterial genera, family and order, and volatiles detected in the nest material and the uropygial secretion of female and nestling hoopoes. Values are PC factor loadings after varimax normalized rotated and in their nest material or nest boxes. Each PC‑axis was named by a composition of letters that indicate the type of samples. The first letter indicates whether the sample corresponds to bacteria (B) or volatiles (V), the second letter indicates whether the sample is from secretions of females (SF), nestlings (SN) or nest material (M). Finally, for types of samples that were collected at the beginning (1) and at the end (2) of the nestling period, the name finished with a number. Only factors than entered in final models explain‑ ing the association between bacterial and volatile profiles are shown. The six bacteria/volatile that better explained (positively and negatively) each axis are shown. TableS8. Multiple regression exploring the effect of the first four PC axes of the volatile profile of nestling and adult females on each of the first four PC axis of the volatile profile of the nest. PC factor were calculated after varimax normalized rotation. Each PC‑axis was named by a composition of letters that indicate the type of samples. The first letter indicates corresponds to volatile samples (V), the second letter indicates whether the sample is from secretions of females (SF), nestlings (SN) or nest material (M). Finally, for types of samples that were collected at the beginning (1) and at the end (2) of the nestling period, the name finished with a number. TableS9. Results of PCA analyses summarizing volatiles detected in the nest material and the uropygial secretion of female and nestling hoopoes. Values are PC factor loadings after varimax normalized rotated and in their nest material or nest boxes. Each PC‑axis was named by a composition of letters that indicate the type of samples. The first letter indicates whether the sample corresponds to bacteria (B) or volatiles (V), the second letter indicates whether the sample is from secretions of females (SF), nestlings (SN) or nest material (M). Finally, for types of samples that were collected at the beginning (1) and at the end (2) of the nestling period, the name finished with a number. Only factors than entered in final models explaining the association between volatile profiles of secretions and nest‑box environment are shown. TableS10. 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