==== Front PeerJ PeerJ peerj peerj PeerJ 2167-8359 PeerJ Inc. San Diego, USA 9970 10.7717/peerj.9970 Ecology Genomics Microbiology Zoology The gut microbiota in the common kestrel (Falco tinnunculus): a report from the Beijing Raptor Rescue Center Guan Yu Wang Hongfang Gong Yinan Ge Jianping Bao Lei baolei@bnu.edu.cn Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering and College of Life Science, Beijing Normal University, Beijing, China Harrison Xavier 1 12 2020 2020 8 e997027 1 2020 26 8 2020 ©2020 Guan et al.2020Guan et al.This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.As a complex microecological system, the gut microbiota plays crucial roles in many aspects, including immunology, physiology and development. The specific function and mechanism of the gut microbiota in birds are distinct due to their body structure, physiological attributes and life history. Data on the gut microbiota of the common kestrel, a second-class protected animal species in China, are currently scarce. With high-throughput sequencing technology, we characterized the bacterial community of the gut from nine fecal samples from a wounded common kestrel by sequencing the V3-V4 region of the 16S ribosomal RNA gene. Our results showed that Proteobacteria (41.078%), Firmicutes (40.923%) and Actinobacteria (11.191%) were the most predominant phyla. Lactobacillus (20.563%) was the most dominant genus, followed by Escherichia-Shigella (17.588%) and Acinetobacter (5.956%). Our results would offer fundamental data and direction for the wildlife rescue. Common Kestrel (Falco tinnunculus)Gut microbiota16S rRNA geneHigh-throughput sequencingNon-invasiveNational Natural Science Foundation of China3177041031570381This work was supported by grants from the National Natural Science Foundation of China 31770410 and 31570381. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. ==== Body Introduction Recent research on host-associated gut microbial communities have revealed their important roles in immunology, physiology and development (Guarner & Malagelada, 2003; Nicholson, Holmes & Wilson, 2005), as well as several basic and critical processes, such as nutrient absorption and vitamins synthesis in both human and animals (Fukuda & Ohno, 2014; Kau et al., 2011; Omahony et al., 2015). Gut microbiota analysis of wild animals is becoming a new method that may provide information for wildlife rescue and animal husbandry. Reports concerning the gut microbiota of other avian species, such as Cooper’s hawk (Accipiter cooperii) (Taylor et al., 2019), bar-headed geese (Anser indicus) (Wang et al., 2017), hooded crane (Grus monacha) (Zhao et al., 2017), Western Gull (Larus occidentalis) (Cockerham et al., 2019), herring gull (Larus argentatus) (Fuirst et al., 2018) and black-legged kittiwake (Rissa tridactyla) (Van Dongen et al., 2013), have increased rapidly. The specific function and mechanism of the gut microbiota in birds are distinct due to their body structure, physiological attributes and life history (Kobayashi, 1969; Williams & Tieleman, 2005; Winter, Johnson & Shaffer, 2006). For example, for most birds, a stable body temperature above ambient temperature ensures a high metabolic rate for the birds needed for flight (O’Mara et al., 2017; Schleucher, 2002; Smit et al., 2016). Streamlined bodies, efficient breathing patterns and relatively short gastrointestinal tracts are also special attributes (Klasing, 1999; Orosz & Lichtenberger, 2011). Meanwhile, the birds’ ability to fly sets them apart from other animals, altering their intestinal microbiota to some extent. However, as a research focus, data on the gut microbiota of the common kestrel are currently very scarce. The common kestrel (Falco tinnunculus) is a small raptor that belongs to Falconidae, which is a family of diurnal birds of prey, including falcons and kestrels. A total of 12 subspecies for common kestrel are distributed widely from the Palearctic to Oriental regions (Cramp & Brooks, 1992). Although listed in the least concern (LC) class by the International Union for Conservation of Nature (IUCN) (BirdLife International, 2016), the common kestrel was listed as state second-class protected animals (Defined by the LAW OF THE PEOPLE’S REPUBLIC OF CHINA ON THE PROTECTION OF WILDLIFE, Chapter II, Article 9) in China. The common kestrel is a typical opportunistic forager that catches small and medium-sized animals, including small mammals, birds, reptiles and some invertebrates (Anthony, 1993; Aparicio, 2000; Village, 2010). Insects such as grasshoppers and dragonflies were also identified in the diet of the common kestrel (Geng et al., 2009). As generalist predators, common kestrels choose distinct predatory strategies when non-breeding and breeding to minimize the expenditure of energy, such as the strategy of the low-cost low-profit technique of perch-hunting in winter, while maximized daily energy gain in summer (Costantini et al., 2005; Masman, Daan & Dijkstra, 1988). Previous studies on common kestrels were comprehensive, such as those on diet and prey selection (Geng et al., 2009; Kirkwood, 1980; Korpimäki, 1985; Lihu et al., 2007; Souttou et al., 2007; Van Zyl, 1994), behavior and diseases (Aschwanden, Birrer & Jenni, 2005; Bustamante, 1994; Hille, Nash & Krone, 2007), and genetic variation and diversity (Nesje et al., 2000; Padilla et al., 2009; Riegert, Fainová & Bystřická, 2010; Zhang, Liu & Song, 2008). As common raptors around the whole world, as well as the important predators in food chains, common kestrels should be studied more deeply with the newer methods and techniques. The aim of this study was to characterize the bacterial community of the gut by sequencing the V3-V4 region of the 16S rRNA gene of a wounded common kestrel. The data we obtained could provide basic information for further conservation and rescue of wild common kestrels. Materials & Methods Fecal samples collection This study is of a single kestrel sampled multiple times with feces at Beijing Raptor Rescue Center (BRRC). The injured common kestrel that could not fly was found in the Fengtai district by a rescuer on June 22nd, 2019 and then taken to the BRRC for professional rescue. The wounded common kestrel was carefully treated with several surgeries and drug therapies. Nine fecal samples (E1–E9) that may reflect the actual state of its health were collected from the common kestrel after relevant treatments on different days. The samples collection information and medical records of the common kestrel were shown in Tables S1–S3 respectively. All samples were transported immediately into the laboratory in an ice box and ultimately stored at −80 °C for further bacterial studies. DNA extraction and PCR amplification Microbial DNA was extracted from fresh fecal samples using an E.Z.N.A.® Stool DNA Kit (Omega Bio-tek, Norcross, GA, U.S.) according to the manufacturer’s protocols. The V3–V4 region of the bacterial 16S ribosomal RNA gene was amplified by PCR (95 °C for 3 min; followed by 25 cycles at 95 °C for 30 s, 55 °C for 30 s, and 72 °C for 30 s; and a final extension at 72 °C for 5 min) using the primers 338F (5′-barcode-ACTCCTACGGGAGGCAGCAG-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′), where the barcode is an eight-base sequence unique to each sample. PCRs were performed in triplicate in a 20  µL mixture containing 4  µL of 5 × FastPfu Buffer, 2  µL of 2.5 mM dNTPs, 0.8 µL of each primer (5 µM), 0.4 µL of FastPfu Polymerase, and 10 ng of template DNA. Illumina MiSeq sequencing Amplicons were extracted from 2% agarose gels and purified using an AxyPrep DNA Gel Extraction Kit (Axygen Biosciences, Union City, CA, U.S.) according to the manufacturer’s instructions and quantified using QuantiFluor™ -ST (Promega, U.S.). Purified amplicons were pooled in equimolar amounts and paired-end sequenced (2 × 250) on an Illumina MiSeq platform according to standard protocols. Processing of sequencing data Raw fastq files were demultiplexed and quality-filtered using QIIME (version 1.17) (Caporaso et al., 2010) with the following criteria. (i) The 300 bp reads were truncated at any site receiving an average quality score <20 over a 50 bp sliding window, discarding the truncated reads that were shorter than 50 bp. (ii) Exact barcode matching, 2 nucleotide mismatches in primer matching, and reads containing ambiguous characters were removed. (iii) Only sequences that overlapped longer than 10 bp were assembled according to their overlap sequence. Reads that could not be assembled were discarded. Operational taxonomic units (OTUs) were clustered with a 97% similarity cutoff using UPARSE (version 7.1 http://drive5.com/uparse/), and chimeric sequences were identified and removed using UCHIME (Edgar et al., 2011). The taxonomy of each 16S rRNA gene sequence was analyzed by RDP Classifier (http://rdp.cme.msu.edu/) against the SILVA (SSU132)16S rRNA database using a confidence threshold of 70% (Amato et al., 2013). Data analysis All the indices of alpha diversity, including Chao, ACE, Shannon, Simpson, and coverage, and the analysis of beta diversity were calculated with QIIME. The rarefaction curves, rank abundance curves, and stacked histogram of relative abundance were displayed with R (R Core Team, 2015). The hierarchical clustering trees were built using UPGMA (unweighted pair-group method with arithmetic mean) based on weighted and unweighted distance matrices at different levels. Principal coordinate analysis (PCoA) was calculated and displayed using QIIME and R, as well as hierarchical clustering trees. This study was performed in accordance with the recommendations of the Animal Ethics Review Committee of Beijing Normal University (approval reference number: CLS-EAW-2019-026). Results Overall sequencing data A total of 28 phyla, 70 classes, 183 orders, 329 families and 681 genera were detected among the gastrointestinal bacterial communities. There were altogether 389,474 reads obtained and classified into 1673 OTUs at the 0.97 sequence identity cut-off in 9 fecal samples from a common kestrel. Alpha diversity indices (including Sobs, Shannon, Simpson, ACE, Chao and coverage) of each sample are shown in Table 1. The Sobs and Shannon index of all samples are shown in Fig. 1. Additionally, the rarefaction curves (A) and the rank abundance curves (B) are shown in Fig. S1, which indicated that the number of OTUs for further analysis was reasonable, as well as the abundance of species in common kestrel feces. The total sequences, total bases and OTU distributions of all samples are shown in Tables S4 and S5. Bacterial composition and relative abundance At the phylum level of the gut microbiota in the common kestrel, the most predominant phylum was Proteobacteria (41.078%), followed by Firmicutes (40.923%), Actinobacteria (11.191%) and Bacteroidetes (3.821%). In addition to Tenericutes (0.178%) and Verrucomicrobia (0.162%), Patescibacteria (0.543%) and Deinococcus-Thermus (0.504%) were also ranked in the top 10 species in the common kestrel fecal microbiota (Table 2). The top five families in the gut microbiota were Lactobacillaceae (20.563%), Enterobacteriaceae (18.346%), Moraxellaceae (6.733%), Bifidobacteriaceae (5.624%) and Burkholderiaceae (4.752%). At the genus level, Lactobacillus (20.563%), Escherichia-Shigella (17.588%) and Acinetobacter (5.956%) were the most dominant genera. These were followed by Bifidobacterium (5.624%) and Enterococcus (4.024%) (Table 3). These five genera in the total gut microbiota of several samples accounted for a small proportion, such as for E5 (28.755%) and E6 (10.905%) and especially for E4 (2.861%), while the largest proportion was 98.416% in E1. The stacked histogram of relative abundance for species is also demonstrated in Fig. 2 at the phylum (A) and genus (B) levels, which could intuitively represent the basic bacterial composition and relative abundance. The community structures of E1 and E9 were more similar than those of the other feces samples at both levels. 10.7717/peerj.9970/table-1Table 1 Alpha diversity of gut microbiota in Common Kestrel feces. Sample Sobs Shannon Simpson Ace Chao Coverage E1 66 0.596 0.788 78.114 73.583 1.000 E2 649 2.780 0.204 674.412 672.193 0.998 E3 515 2.965 0.184 524.452 522.519 0.999 E4 578 4.233 0.053 594.498 594.050 0.999 E5 235 3.285 0.057 448.368 378.103 0.997 E6 476 4.802 0.020 479.110 480.091 1.000 E7 263 1.604 0.399 292.553 281.800 0.999 E8 317 2.706 0.143 364.651 359.519 0.998 E9 317 2.374 0.335 330.906 331.607 0.999 The hierarchical clustering trees showed the similarity of community structure among different samples, which were generated by UPGMA (unweighted pair-group method with arithmetic mean) with the unweighted UniFrac (Fig. 3A) and weighted UniFrac (Fig. 3B) distance matrixes. Although the fecal samples were collected from the common kestrel in chronological order (E1–E9) of therapy treatments, no distinct or obvious clustering relationships are discernable in Fig. 3. 10.7717/peerj.9970/fig-1Figure 1 Sobs index (A) and the Shannon index (B) of samples. 10.7717/peerj.9970/table-2Table 2 The relative abundance of species in gut microbiota of Common Kestrel at phylum level. The names of phyla in Table 2 represented Proteobacteria, Firmicutes, Actinobacteria, Bacteroidetes, Patescibacteria, Deinococcus-Thermus, unclassified_K_norank_d_Bacteria, Tenericutes, Verrucomicrobia, respectively. Sample Pro Fir Act Bac Pat Dei unc Ten Ver Others E1 88.630% 10.634% 0.623% 0.006% 0.003% 0.000% 0.096% 0.000% 0.006% 0.003% E2 13.211% 79.816% 2.376% 1.085% 0.085% 0.065% 0.361% 1.291% 0.017% 1.694% E3 50.540% 39.567% 3.286% 1.502% 1.857% 0.087% 1.553% 0.121% 0.011% 1.474% E4 73.770% 3.574% 8.602% 5.950% 1.719% 3.960% 0.220% 0.008% 0.158% 2.038% E5 27.797% 43.152% 10.694% 18.166% 0.104% 0.042% 0.006% 0.000% 0.000% 0.039% E6 36.410% 30.610% 20.330% 5.572% 0.944% 0.324% 1.511% 0.135% 1.223% 2.940% E7 5.000% 73.097% 20.770% 0.676% 0.003% 0.000% 0.076% 0.000% 0.006% 0.372% E8 11.832% 59.652% 27.752% 0.369% 0.073% 0.003% 0.031% 0.000% 0.031% 0.256% E9 62.507% 28.205% 6.285% 1.065% 0.096% 0.056% 0.671% 0.045% 0.006% 1.063% Mean 41.078% 40.923% 11.191% 3.821% 0.543% 0.504% 0.503% 0.178% 0.162% 1.098% 10.7717/peerj.9970/table-3Table 3 The relative abundance of species in gut microbiota of Common Kestrel at genus level. The names of phyla in Table 3 represented Lactobacillus, Escherichia-Shigella, Acinetobacter, Bifidobacterium, Enterococcus, Clostridium_sensu_stricto_1, Paracoccus, Burkholderia- Caballeronia-Paraburkholderia, Glutamicibacter, respectively. Sample Lac Esc Aci Bif Ent Clo Par Bur Glu Others E1 6.618% 88.610% 0.011% 0.037% 3.140% 0.023% 0.000% 0.000% 0.000% 1.561% E2 68.336% 1.787% 0.581% 0.034% 2.528% 0.042% 0.017% 5.567% 0.042% 21.066% E3 24.037% 0.862% 38.448% 0.093% 0.448% 0.707% 0.101% 5.544% 0.023% 29.736% E4 0.392% 0.166% 2.153% 0.031% 0.118% 0.214% 19.488% 0.854% 0.860% 75.724% E5 0.693% 7.962% 5.040% 0.034% 15.026% 0.011% 0.149% 0.014% 9.411% 61.659% E6 1.356% 0.130% 5.823% 3.086% 0.510% 1.043% 6.023% 4.445% 6.113% 71.470% E7 66.056% 0.054% 0.211% 20.356% 2.120% 0.192% 0.031% 2.841% 0.011% 8.129% E8 9.589% 1.536% 0.536% 25.502% 8.988% 28.177% 0.054% 2.060% 0.099% 23.459% E9 7.988% 57.183% 0.798% 1.446% 3.340% 1.866% 0.273% 0.347% 0.000% 26.759% Mean 20.563% 17.588% 5.956% 5.624% 4.024% 3.586% 2.904% 2.408% 1.840% 35.507% 10.7717/peerj.9970/fig-2Figure 2 The histogram of relative abundance for species in Common Kestrel at phylum (A) and genus (B) level. 10.7717/peerj.9970/fig-3Figure 3 The hierarchical clustering trees. (A) and (B) were generated based on unweighted and weighted distance matrix at phylum level, respectively. Discrepancy of community composition To further demonstrate the differences in community composition among the nine samples, principal coordinates analysis (PCoA) was applied (Fig. 4). For PCoA, we chose the same two distance matrices (unweighted UniFrac in Fig. 4A and weighted UniFrac in Fig. 4B) as above to analyze the discrepancies. The results in Fig. 4 were similar to those in Fig. 3, in which all samples scattered dispersedly, suggesting that variation in the composition of the gut microbiota of the common kestrel was not obvious over time. 10.7717/peerj.9970/fig-4Figure 4 PCoA of the bacterial population structures. The different shape with colors represented all samples of Common Kestrel respectively. For PCoA, (A) was generated with unweighted Unifrac distance while (B) used weighted Unifrac distance. Discussion Knowledge and comprehension concerning gut microbiota have continued to progressively develop with relevant techniques over the past decade (Guarner, 2014; Li et al., 2014; Qin et al., 2010). The application of analysis for intestinal microecology continues to be also a research focus in the field of wildlife rescue. The common kestrel (Falco tinnunculus) is listed as a second-class protected animal species in China. Although research concerning avian species, including the common kestrel, has been increasing gradually, the available data on the gut microbiota in the common kestrel were currently unknown. We characterized the basic composition and structure of the gut microbiota from a wounded common kestrel in this study, which was rescued by the Beijing Raptor Rescue Center (BRRC). In general, the overall community structure of the gut microbiota in this common kestrel was in accordance with previous relevant characterizations in birds, such as Cooper’s hawks (Taylor et al., 2019), bar-headed geese (Wang et al., 2017), hooded cranes (Zhao et al., 2017) and swan geese (Wang et al., 2016), which included Proteobacteria, Firmicutes, Actinobacteria and Bacteroidetes. The most predominant phylum in the fecal gut microbiota of the common kestrel was Proteobacteria (41.078%), which ranked after Firmicutes in other birds, such as cockatiels (Nymphicus hollandicus) (Alcaraz, Hernández & Peimbert, 2016) and black-legged kittiwakes (Van Dongen et al., 2013). This crucial phylum plays many valuable roles. For instance, Proteobacteria is beneficial for the giant panda, which can degrade lignin in its major food resource (Fang et al., 2012). Additionally, it has been reported that Proteobacteria is also the most dominant phylum in obese dogs (Park et al., 2015). The specific function of this phylum could be distinct in birds due to their unique physiological traits, as well as their developmental strategies (Kohl, 2012). However, the high relative abundance of Proteobacteria in the total bacterial community was observed mainly in several samples that were collected during surgeries or drug treatments, such as E1 and E4. Sample E1 was collected on 23rd June that the day after the kestrel rescued from the wild. On 22nd June, the kestrel was bandaged with silver sulfadiazine cream (SSD), also subcutaneously injected with 10 ml and orally administered with 4ml lactated ringer’s solution (LRS) respectively. The increased level of Proteobacteria was associated with some cardiovascular events, inflammation and inflammatory bowel disease (Amar et al., 2013; Carvalho et al., 2012). Although the kestrel’s weight increased 34 grams when E4 was collected, it just ate a mouse’s head. Combined with the status when the kestrel was rescued, we speculated that the increased proportion of Proteobacteria may reflect its food consumption or gastrointestinal status to some extent. Environmental influential factors, as well as dietary changes, should also be considered an important index that could result in variations in the relative abundance of species in the gut microbiota (De Filippo et al., 2010; Scott et al., 2013). Furthermore, the dominant genera within Proteobacteria in our study were Escherichia-Shigella (17.588%), Acinetobacter (5.956%), Paracoccus (2.904%) and Burkholderia-Caballeronia-Paraburkholderia (2.408%). Escherichia-Shigella is a common pathogenic bacterium that can cause diarrhea in humans (Hermes et al., 2009). The main cause for the high relative abundance of Escherichia-Shigella was the E1 (88.610%) sample, which suggested indirectly that the physical condition of the common kestrel was not normal when it was rescued by staff from the BRRC. This result was also consistent with the actual state of this wounded common kestrel that we observed (Table S3). Although Firmicutes (40.923%) ranked after Proteobacteria, its actual relative abundance was only slightly lower than that in the common kestrel. As a common phylum of the gut microbiota, Firmicutes exists widely in both mammals and birds, and this ancient symbiosis may be linked to the common ancestor of amniotes (Costello et al., 2010; Kohl, 2012). Firmicutes can provide certain energy for the host through catabolizing complex carbohydrates, sugar, and even by digesting fiber in some species (Costa et al., 2012; Flint et al., 2008; Guan et al., 2017). The dominant genera in Firmicutes were Lactobacillus (20.563%), Enterococcus (4.024%) and Clostridium_sensu_stricto_1 (3.586%). The relative abundance of Enterococcus in E5 (15.026%) contributed to the highest ranking of this genus. Enterococcus is not regarded as a pathogenic bacterium due to its harmlessness and can even be used as a normal food additive in related industries (Fisher & Phillips, 2009; Moreno et al., 2006). Enterococcus species are also considered common nosocomial pathogens that can cause a high death rate (Lopes et al., 2005). Meanwhile, these species are also associated with certain infections, including neonatal infections, intraabdominal and pelvic infections, as well as the nosocomial infections and superinfections (Murray, 1990). Coincidentally, prior to the collection of sample E5, the kestrel was anesthetized for the treatment of the right tarsometatarsus injury. The right digit tendon of the kestrel was exposed before managing the wound, without any function. Although ensuring the sterile conditions, we inferred that the kestrel was infected by certain bacteria during the surgery. The BRRC could be regarded as a specific hospital for raptor, which could explain the high proportion of Enterococcus in the fecal samples of this common kestrel. However, this genus should be given sufficient attention in subsequent studies with additional samples from different individuals. The abundance of Clostridium increases as more protein is digested (Lubbs et al., 2009). Clostridium difficile has been reported to be associated with certain diseases, such as diarrhea and severely life-threatening pseudomembranous colitis (Kuijper, Coignard & Tull, 2006; Pepin et al., 2004). The high relative abundance of this genus also resulted primarily from certain samples (E8, 28.177%), similar to the Enterococcus mentioned above. And it’s remarkable that the collection of sample E8 was in the same situation as E5. On 13th July, the kestrel also underwent surgery under anesthesia. While E5 was collected, the kestrel’s status was still normal according to relevant records. These results indicated that the high relative abundance of certain pathogens may not show any symptoms of illness for the kestrel. In general, the abnormal situation of E5 and E8 still need to be paid enough attention. Moreover, to minimize the influences due to the individual differences, more samples from different individuals should be collected for further study. The third dominant phylum in the gut microbiota in our study was Actinobacteria (11.191%), which was also detected in other species, such as turkeys (Meleagris gallopavo) (Wilkinson et al., 2017) and Leach’s storm petrel (Oceanodroma leucorhoa) (Pearce et al., 2017). The relative abundance of Actinobacteria varied in different species, such as house cats (7.30%) and dogs (1.8%) (Handl et al., 2011), but only accounted for 0.53% in wolves (Wu et al., 2017). Within this phylum, Bifidobacterium (5.624%) and Glutamicibacter (1.840%) were the primary genera. The presence of Bifidobacterium is closely related to the utilization of glycans produced by the host, as well as oligosaccharides in human milk (Sela et al., 2008; Turroni et al., 2010). Noticeably, Bifidobacterium thermophilum was reported to be used through oral administration for chickens to resist E. coli infection (Kobayashi et al., 2002). The detection and application of Bifidobacterium, especially for the rescue of many rare avian species, would be worth considering for curing various diseases in the future. Additionally, the relative abundance of Bacteroidetes was 3.821% in this study, which consisted mainly of Sphingobacterium. Bacteroidetes is another important component of the gut microbiota that can degrade relevant carbohydrates from secretions of the gut, as well as high molecular weight substances (Thoetkiattikul et al., 2013). The proportion of Bacteroidetes, which was stable in most samples we collected except E5 (18.166%), would increase correspondingly with weight loss for mice or changes in fiber content in rural children’s daily diet (De Filippo et al., 2010; Ley et al., 2006; Turnbaugh et al., 2008). However, the weight of the kestrel was increasing during the collection of E5 and E8. Additionally, although the kestrel underwent surgery on 4th July, the reason for the high proportion of Bacteroidetes in its fecal sample E5 were unclear. To characterize the basic composition and structure of the gut microbiota for the common kestrel more accurately, additional fresh fecal samples from healthy individuals should be collected in follow-up studies. Furthermore, additional attention should be paid to the high ranking of Patescibacteria (0.543%) and Deinococcus-Thermus (0.504%) at the phylum level. Patescibacteria might be related to basic biosynthesis of amino acids, nucleotides and so on (Lemos et al., 2019). Members of Deinococcus-Thermus are known mainly for their capability to resist extreme radiation, including ultraviolet radiation, as well as oxidizing agents (Cox & Battista, 2005; Griffiths & Gupta, 2007). The specific function of certain species in these phyla for the common kestrel should be studied by controlled experiments, detailed observations or more advanced approaches, as molecular biological techniques are developed. In addition to the quantity of samples, living environment, age, sex and individual differentiation should also be considered as influencing factors, which would cause a degree of discrepancies at all levels in the gut microbiota. In addition, A comparison of wounded and healthy samples for the bacterial composition in the intestinal microbiota is another essential research direction that may provide additional information for wild animal rescue, such as important biomarkers that indirectly indicate potential diseases. Conclusion In summary, using high-throughput sequencing technology in this study, we first characterized the elementary bacterial composition and structure of the gut microbiota for a wounded common kestrel in the BRRC, which could provide valuable basic data for future studies. Further research on Enterococcus, Patescibacteria and Deinococcus-Thermus should be conducted in the future with additional samples. The integration of other auxiliary techniques or disciplines, such as metagenomics and transcriptomics, could offer a deeper understanding of the function and mechanism of the gut microbiota, as well as the wildlife rescue. Supplemental Information 10.7717/peerj.9970/supp-1Table S1 Collection Date of Samples Click here for additional data file. 10.7717/peerj.9970/supp-2Table S2 Common abbreviations in the medical records Click here for additional data file. 10.7717/peerj.9970/supp-3Table S3 Medical records for the wound common kestrel Click here for additional data file. 10.7717/peerj.9970/supp-4Table S4 Total sequences, total bases of samples Click here for additional data file. 10.7717/peerj.9970/supp-5Table S5 OTU distributions of samples Click here for additional data file. 10.7717/peerj.9970/supp-6Figure S1 Rarefaction Curves (A) reflect the rationality of the size for sequencing data, also the bacterial diversity of each sample Rank Abundance Curves (B) reflect the species richness by the span of curves onthehorizontal axis. While the evenness of the bacterial communities was depicted by the shape of curves. Click here for additional data file. We sincerely thank the Beijing Raptor Rescue Center (BRRC) and Professor Limin Feng for sample collection of from the common kestrel. Additional Information and Declarations Competing Interests The authors declare there are no competing interests. Author Contributions Yu Guan and Lei Bao conceived and designed the experiments, analyzed the data, prepared figures and/or tables, authored or reviewed drafts of the paper, and approved the final draft. Hongfang Wang performed the experiments, authored or reviewed drafts of the paper, and approved the final draft. Yinan Gong performed the experiments, analyzed the data, prepared figures and/or tables, and approved the final draft. Jianping Ge conceived and designed the experiments, authored or reviewed drafts of the paper, and approved the final draft. Animal Ethics The following information was supplied relating to ethical approvals (i.e., approving body and any reference numbers): The study was approved by the Animal Ethics Review Committee at Beijing Normal University (CLS-EAW-2019-026). DNA Deposition The following information was supplied regarding the deposition of DNA sequences: The data for our study are available in the NCBI Sequence Read Archive (SRA): PRJNA599118. Data are also available at figshare: Guan, Yu (2020). “Raw data”. figshare. Dataset https://doi.org/10.6084/m9.figshare.11691957.v1. ==== Refs References Alcaraz, Hernández & Peimbert (2016) Alcaraz LD Hernández AM Peimbert M 2016 Exploring the cockatiel (Nymphicus hollandicus ) fecal microbiome, bacterial inhabitants of a worldwide pet PeerJ 4 e2837 10.7717/peerj.2837 28028487 Amar et al. (2013) Amar J Lange C Payros G Garret C Chabo C Lantieri O Courtney M Marre M Charles M Balkau B Burcelin R 2013 Blood microbiota dysbiosis is associated with the onset of cardiovascular events in a large general population: the D.E.S.I.R. study PLOS ONE 8 1 e54461 10.1371/journal.pone.0054461 23372728 Amato et al. (2013) Amato KR Yeoman CJ Kent A Righini N Carbonero F Estrada A Gaskins HR Stumpf RM Yildirim S Torralba M 2013 Habitat degradation impacts black howler monkey (Alouatta pigra ) gastrointestinal microbiomes ISME Journal 7 7 1344 1353 10.1038/ismej.2013.16 23486247 Anthony (1993) Anthony V 1993 Foraging of the South African Rock Kestrel (Falco tinnunculus rupicolus ) Biology and conservation of small falcons London Hawk and Owl Trust 151 162 Aparicio (2000) Aparicio JM 2000 Differences in the diets of resident and non-resident Kestrels in Spain Ornis Fennica 77 169 175 Aschwanden, Birrer & Jenni (2005) Aschwanden J Birrer S Jenni L 2005 Are ecological compensation areas attractive hunting sites for common kestrels (Falco tinnunculus ) and long-eared owls (Asio otus )? Journal of Ornithology 146 279 286 10.1007/s10336-005-0090-9 BirdLife International (2016) BirdLife International 2016 Falco tinnunculus . The IUCN Red List of Threatened Species 2016: e.T22696362A93556429 Downloaded on 09 August 2020 10.2305/IUCN.UK.2016-3.RLTS.T22696362A93556429.en Bustamante (1994) Bustamante J 1994 Behavior of colonial common kestrels (Falco tinnunculus ) during the post-fledging dependence period in southwestern Spain Journal of Raptor Research 28 79 83 Caporaso et al. (2010) Caporaso JG Kuczynski J Stombaugh J Bittinger K Bushman FD Costello EK Fierer N Pena AG Goodrich JK Gordon JI 2010 QIIME allows analysis of high-throughput community sequencing data Nature Methods 7 5 335 336 10.1038/nmeth.f.303 20383131 Carvalho et al. (2012) Carvalho FA Koren O Goodrich JK Johansson MEV Nalbantoglu I Aitken JD Su Y Chassaing B Walters WA Gonzalez A 2012 Transient inability to manage proteobacteria promotes chronic gut inflammation in TLR5-deficient mice Cell Host & Microbe 12 139 152 10.1016/j.chom.2012.07.004 22863420 Cockerham et al. (2019) Cockerham S Lee B Orben R Suryan R Torres L Warzybok P Bradley R Jahncke J Young H Ouverney C Shaffer S 2019 Microbial ecology of the western gull (Larus occidentalis ) Microbial Ecology 78 3 665 676 10.1007/s00248-019-01352-4 30891612 Costa et al. (2012) Costa MC Arroyo LG Allen-Vercoe E Stämpfli HR Kim PT Sturgeon A Weese JS 2012 Comparison of the fecal microbiota of healthy horses and horses with colitis by high throughput sequencing of the V3-V5 region of the 16S rRNA gene PLOS ONE 7 e41484 10.1371/journal.pone.0041484 22859989 Costantini et al. (2005) Costantini D Casagrande S Di Lieto G Fanfani A Dell’Omo G 2005 Consistent differences in feeding habits between neighbouring breeding kestrels Behaviour 142 1409 1421 Costello et al. (2010) Costello EK Gordon JI Secor SM Knight R 2010 Postprandial remodeling of the gut microbiota in Burmese pythons ISME Journal 4 11 1375 1385 10.1038/ismej.2010.71 20520652 Cox & Battista (2005) Cox MM Battista JR 2005 Deinococcus radiodurans—the consummate survivor Nature Reviews: Microbiology 3 11 882 892 16261171 Cramp & Brooks (1992) Cramp S Brooks D 1992 Handbook of the birds of Europe, the Middle East and North Africa The birds of the western Palearctic, V.I. Warblers vol. VI Oxford University Press Oxford De Filippo et al. (2010) De Filippo C Cavalieri D Di Paola M Ramazzotti M Poullet JB Massart S Collini S Pieraccini G Lionetti P 2010 Impact of diet in shaping gut microbiota revealed by a comparative study in children from Europe and rural Africa Proceedings of the National Academy of Sciences of the United States of America 107 14691 14696 10.1073/pnas.1005963107 20679230 Edgar et al. (2011) Edgar RC Haas BJ Clemente JC Quince C Knight R 2011 UCHIME improves sensitivity and speed of chimera detection Bioinformatics 27 2194 2200 10.1093/bioinformatics/btr381 21700674 Fang et al. (2012) Fang W Fang Z Zhou P Chang F Hong Y Zhang X Peng H Xiao Y 2012 Evidence for lignin oxidation by the giant panda fecal microbiome PLOS ONE 7 e50312 10.1371/journal.pone.0050312 23209704 Fisher & Phillips (2009) Fisher K Phillips C 2009 The ecology, epidemiology and virulence of Enterococcus Microbiology 155 1749 1757 10.1099/mic.0.026385-0 19383684 Flint et al. (2008) Flint HJ Bayer EA Rincon MT Lamed R White BA 2008 Polysaccharide utilization by gut bacteria: potential for new insights from genomic analysis Nature Reviews: Microbiology 6 2 121 131 18180751 Fuirst et al. (2018) Fuirst M Veit RR Hahn M Dheilly NM Thorne LH 2018 Effects of urbanization on the foraging ecology and microbiota of the generalist seabird Larus argentatus PLOS ONE 13 12 e0209200 10.1371/journal.pone.0209200 30562368 Fukuda & Ohno (2014) Fukuda S Ohno H 2014 Gut microbiome and metabolic diseases Seminars in Immunopathology 36 103 114 10.1007/s00281-013-0399-z 24196453 Geng et al. (2009) Geng R Zhang X Ou W Sun H Lei F Gao W Wang H 2009 Diet and prey consumption of breeding Common Kestrel (Falco tinnunculus ) in Northeast China Progress in Natural Science 19 1501 1507 10.1016/j.pnsc.2009.03.011 Griffiths & Gupta (2007) Griffiths E Gupta RS 2007 Identification of signature proteins that are distinctive of the Deinococcus-Thermus phylum International Microbiology 10 3 201 208 18076002 Guan et al. (2017) Guan Y Yang H Han S Feng L Wang T Ge J 2017 Comparison of the gut microbiota composition between wild and captive sika deer (Cervus nippon hortulorum ) from feces by high-throughput sequencing AMB Express 7 212 10.1186/s13568-017-0517-8 29170893 Guarner (2014) Guarner F 2014 Decade in review—gut microbiota: the gut microbiota era marches on Nature Reviews Gastroenterology & Hepatology 11 647 649 10.1038/nrgastro.2014.156 Guarner & Malagelada (2003) Guarner F Malagelada J-R 2003 Gut flora in health and disease The Lancet 361 512 519 10.1016/S0140-6736(03)12489-0 Handl et al. (2011) Handl S Dowd SE Garcia-Mazcorro JF Steiner JM Suchodolski JS 2011 Massive parallel 16S rRNA gene pyrosequencing reveals highly diverse fecal bacterial and fungal communities in healthy dogs and cats FEMS Microbiology Ecology 76 301 310 10.1111/j.1574-6941.2011.01058.x 21261668 Hermes et al. (2009) Hermes RG Molist F Ywazaki M Nofrarías M Gomez de Segura A Gasa J Pérez J 2009 Effect of dietary level of protein and fiber on the productive performance and health status of piglets Journal of Animal Science 87 3569 3577 10.2527/jas.2008-1241 19648494 Hille, Nash & Krone (2007) Hille SM Nash JP Krone O 2007 Hematozoa in endemic subspecies of common kestrel in the Cape Verde Islands Journal of Wildlife Diseases 43 752 757 10.7589/0090-3558-43.4.752 17984275 Kau et al. (2011) Kau AL Ahern PP Griffin NW Goodman AL Gordon JI 2011 Human nutrition, the gut microbiome and the immune system Nature 474 327 336 10.1038/nature10213 21677749 Kirkwood (1980) Kirkwood JK 1980 Management of a colony of common kestrels (Falco tinnunculus ) in captivity Laboratory Animals 14 313 316 10.1258/002367780781071148 7464019 Klasing (1999) Klasing KC 1999 Avian gastrointestinal anatomy and physiology Seminars in Avian and Exotic Pet Medicine 8 42 50 10.1016/S1055-937X(99)80036-X Kobayashi et al. (2002) Kobayashi C Yokoyama H Nguyen SV Hashi T Kuroki M Kodama Y 2002 Enhancement of chicken resistance against Escherichia coli infection by oral administration of Bifidobacterium thermophilum preparations Avian Diseases 46 542 546 10.1637/0005-2086(2002)046[0542:EOCRAE]2.0.CO;2 12243516 Kobayashi (1969) Kobayashi S 1969 On the fine structure of the carotid body of the bird, Uroloncha domestica Archives of Histology and Cytology 31 9 19 Kohl (2012) Kohl KD 2012 Diversity and function of the avian gut microbiota Journal of Comparative Physiology B: Biochemical, Systemic, and Environmental Physiology 182 591 602 10.1007/s00360-012-0645-z Korpimäki (1985) Korpimäki E 1985 Diet of the Kestrel Falco tinnunculus in the breeding season Ornis Fennica 62 130 137 Kuijper, Coignard & Tull (2006) Kuijper EJ Coignard B Tull P 2006 Emergence of Clostridium difficile-associated disease in North America and Europe Clinical Microbiology and Infection 12 2 18 Lemos et al. (2019) Lemos LN Medeiros JD Dini-Andreote F Fernandes GR Varani AM Oliveira G Pylro VS 2019 Genomic signatures and co-occurrence patterns of the ultra-small Saccharimonadia (phylum CPR/Patescibacteria) suggest a symbiotic lifestyle Molecular Ecology 28 4259 4271 10.1111/mec.15208 31446647 Ley et al. (2006) Ley RE Turnbaugh PJ Klein S Gordon JI 2006 Microbial ecology: human gut microbes associated with obesity Nature 444 7122 1022 1023 10.1038/4441022a 17183309 Li et al. (2014) Li J Jia H Cai X Zhong H Feng Q Sunagawa S Arumugam M Kultima JR Prifti E Nielsen T 2014 An integrated catalog of reference genes in the human gut microbiome Nature Biotechnology 32 834 841 10.1038/nbt.2942 Lihu et al. (2007) Lihu X Jianjian L Chunfu T Wenshan H 2007 Foraging area and hunting technique selection of Common Kestrel (Falco tinnunculus ) in winter: the role of perch sites Acta Ecologica Sinica 27 2160 2166 10.1016/S1872-2032(07)60046-8 Lopes et al. (2005) Lopes MDFS Ribeiro T Abrantes M Marques JJF Tenreiro R Crespo MTB 2005 Antimicrobial resistance profiles of dairy and clinical isolates and type strains of enterococci International Journal of Food Microbiology 103 191 198 10.1016/j.ijfoodmicro.2004.12.025 16083821 Lubbs et al. (2009) Lubbs D Vester B Fastinger N Swanson KS 2009 Dietary protein concentration affects intestinal microbiota of adult cats: a study using DGGE and qPCR to evaluate differences in microbial populations in the feline gastrointestinal tract Journal of Animal Physiology and Animal Nutrition 93 113 121 10.1111/j.1439-0396.2007.00788.x 19386015 Masman, Daan & Dijkstra (1988) Masman D Daan S Dijkstra C 1988 Time allocation in the kestrel (Falco tinnunculus ), and the principle of energy minimization Journal of Animal Ecology 57 2 411 432 Moreno et al. (2006) Moreno MF Sarantinopoulos P Tsakalidou E De Vuyst L 2006 The role and application of enterococci in food and health International Journal of Food Microbiology 106 1 24 10.1016/j.ijfoodmicro.2005.06.026 16216368 Murray (1990) Murray BE 1990 The life and times of the Enterococcus Clinical Microbiology Reviews 3 46 65 10.1128/CMR.3.1.46 2404568 Nesje et al. (2000) Nesje M Røed K Lifjeld J Lindberg P Steen O 2000 Genetic relationships in the peregrine falcon (Falco peregrinus ) analysed by microsatellite DNA markers Molecular Ecology 9 53 60 10.1046/j.1365-294x.2000.00834.x 10652075 Nicholson, Holmes & Wilson (2005) Nicholson JK Holmes E Wilson ID 2005 Gut microorganisms, mammalian metabolism and personalized health care Nature Reviews: Microbiology 3 431 438 15821725 Omahony et al. (2015) Omahony SM Clarke G Borre YE Dinan TG Cryan JF 2015 Serotonin, tryptophan metabolism and the brain-gut-microbiome axis Behavioural Brain Research 277 32 48 10.1016/j.bbr.2014.07.027 25078296 O’Mara et al. (2017) O’Mara MT Wikelski M Voigt CC Ter Maat A Pollock HS Burness G Desantis LM Dechmann DKN 2017 Cyclic bouts of extreme bradycardia counteract the high metabolism of frugivorous bats eLife 6 e26686 10.7554/eLife.26686.002 28923167 Orosz & Lichtenberger (2011) Orosz SE Lichtenberger M 2011 Avian respiratory distress: etiology, diagnosis, and treatment Veterinary Clinics of North America: Exotic Animal Practice 14 241 255 21601813 Padilla et al. (2009) Padilla J Parejo J Salazar J Martínez-Trancón M Rabasco A Sansinforiano E Quesada A 2009 Isolation and characterization of polymorphic microsatellite markers in lesser kestrel (Falco naumanni ) and cross-amplification in common kestrel (Falco tinnunculus ) Conservation Genetics 10 1357 10.1007/s10592-008-9711-1 Park et al. (2015) Park HJ Lee SE Kim HB Isaacson R Seo KW Song KH 2015 Association of obesity with serum leptin, adiponectin, and serotonin and gut microflora in beagle dogs Journal of Veterinary Internal Medicine 29 43 50 10.1111/jvim.12455 25407880 Pearce et al. (2017) Pearce DS Hoover BA Jennings S Nevitt GA Docherty KM 2017 Morphological and genetic factors shape the microbiome of a seabird species (Oceanodroma leucorhoa ) more than environmental and social factors Microbiome 5 146 10.1186/s40168-017-0365-4 29084611 Pepin et al. (2004) Pepin J Valiquette L Alary M Villemure P Pelletier A Forget K Pepin K Chouinard D 2004 Clostridium difficile-associated diarrhea in a region of Quebec from 1991 to 2003: a changing pattern of disease severity Canadian Medical Association Journal 171 466 472 10.1503/cmaj.1041104 15337727 Qin et al. (2010) Qin J Li R Raes J Arumugam M Burgdorf KS Manichanh C Nielsen T Pons N Levenez F Yamada T 2010 A human gut microbial gene catalogue established by metagenomic sequencing Nature 464 59 65 10.1038/nature08821 20203603 R Core Team (2015) R Core Team 2015 R: a language and environment for statistical computing R Foundation for Statistical Computing Vienna http://www.R-project.org/ Riegert, Fainová & Bystřická (2010) Riegert J Fainová D Bystřická D 2010 Genetic variability, body characteristics and reproductive parameters of neighbouring rural and urban common kestrel (Falco tinnuculus ) populations Population Ecology 52 73 79 10.1007/s10144-009-0168-y Schleucher (2002) Schleucher E 2002 Metabolism, body temperature and thermal conductance of fruit-doves (Aves: Columbidae, Treroninae) Comparative Biochemistry and Physiology Part A: Molecular & Integrative Physiology 131 417 428 10.1016/S1095-6433(01)00499-8 Scott et al. (2013) Scott KP Gratz SW Sheridan PO Flint HJ Duncan SH 2013 The influence of diet on the gut microbiota Pharmacological Research 69 52 60 10.1016/j.phrs.2012.10.020 23147033 Sela et al. (2008) Sela D Chapman J Adeuya A Kim J Chen F Whitehead T Lapidus A Rokhsar D Lebrilla CB German J 2008 The genome sequence of Bifidobacterium longum subsp. infantis reveals adaptations for milk utilization within the infant microbiome Proceedings of the National Academy of Sciences of the United States of America 105 18964 18969 10.1073/pnas.0809584105 19033196 Smit et al. (2016) Smit B Zietsman G Martin RO Cunningham SJ McKechnie AE Hockey PAR 2016 Behavioural responses to heat in desert birds: implications for predicting vulnerability to climate warming Climate Change Responses 3 9 10.1186/s40665-016-0023-2 Souttou et al. (2007) Souttou K Baziz B Doumandji S Denys C Brahimi R 2007 Prey selection in the common kestrel, Falco tinnunculus (Aves, Falconidae) in the Algiers suburbs (Algeria) Folia Zoologica 56 4 405 415 Taylor et al. (2019) Taylor MJ Mannan RW U’Ren JM Garber NP Gallery RE Arnold AE 2019 Age-related variation in the oral microbiome of urban Cooper’s hawks (Accipiter cooperii ) BMC Microbiology 19 47 10.1186/s12866-019-1413-y 30791867 Thoetkiattikul et al. (2013) Thoetkiattikul H Mhuantong W Laothanachareon T Tangphatsornruang S Pattarajinda V Eurwilaichitr L Champreda V 2013 Comparative analysis of microbial profiles in cow rumen fed with different dietary fiber by tagged 16S rRNA gene pyrosequencing Current Microbiology 67 130 137 10.1007/s00284-013-0336-3 23471692 Turnbaugh et al. (2008) Turnbaugh PJ Bäckhed F Fulton L Gordon JI 2008 Diet-induced obesity is linked to marked but reversible alterations in the mouse distal gut microbiome Cell Host & Microbe 3 213 223 10.1016/j.chom.2008.02.015 18407065 Turroni et al. (2010) Turroni F Bottacini F Foroni E Mulder I Kim J-H Zomer A Sánchez B Bidossi A Ferrarini A Giubellini V 2010 Genome analysis of Bifidobacterium bifidum PRL2010 reveals metabolic pathways for host-derived glycan foraging Proceedings of the National Academy of Sciences of the United States of America 107 19514 19519 10.1073/pnas.1011100107 20974960 Van Zyl (1994) Van Zyl A 1994 A comparison of the diet of the Common kestrel Falco tinnunculus in South Africa and Europe Bird Study 41 127 130 10.1080/00063659409477208 Van Dongen et al. (2013) Van Dongen WF White J Brandl HB Moodley Y Merkling T Leclaire S Blanchard P Danchin É Hatch SA Wagner RH 2013 Age-related differences in the cloacal microbiota of a wild bird species BMC Ecology 13 11 10.1186/1472-6785-13-11 23531085 Village (2010) Village A 2010 The kestrel London T & AD Poyser Wang et al. (2016) Wang W Zheng S Sharshov K Cao J Sun H Yang F Wang X Li L 2016 Distinctive gut microbial community structure in both the wild and farmed Swan goose (Anser cygnoides ) Journal of Basic Microbiology 56 1299 1307 10.1002/jobm.201600155 27365218 Wang et al. (2017) Wang W Zheng S Sharshov K Sun H Yang F Wang X Li L Xiao Z 2017 Metagenomic profiling of gut microbial communities in both wild and artificially reared Bar-headed goose (Anser indicus ) MicrobiologyOpen 6 e00429 10.1002/mbo3.429 Wilkinson et al. (2017) Wilkinson TJ Cowan A Vallin H Onime L Oyama LB Cameron S Gonot C Moorby J Waddams K Theobald V 2017 Characterization of the microbiome along the gastrointestinal tract of growing turkeys Frontiers in Microbiology 8 1089 10.3389/fmicb.2017.01089 28690591 Williams & Tieleman (2005) Williams JB Tieleman BI 2005 Physiological adaptation in desert birds Bioscience 55 416 425 10.1641/0006-3568(2005)055[0416:PAIDB]2.0.CO;2 Winter, Johnson & Shaffer (2006) Winter M Johnson DH Shaffer JA 2006 Does body size affect a bird’s sensitivity to patch size and landscape structure? The Condor 108 808 816 10.1650/0010-5422(2006)108[808:DBSAAB]2.0.CO;2 Wu et al. (2017) Wu X Zhang H Chen J Shang S Yan J Chen Y Tang X Zhang H 2017 Analysis and comparison of the wolf microbiome under different environmental factors using three different data of Next Generation Sequencing Scientific Reports 7 11332 10.1038/s41598-017-11770-4 28900198 Zhang, Liu & Song (2008) Zhang L Liu Y Song J 2008 Genetic variation between subspecies of common kestrels (Falco Tinnunculus ) in Beijing, China Journal of Raptor Research 42 214 220 10.3356/JRR-07-18.1 Zhao et al. (2017) Zhao G Zhou L Dong Y Cheng Y Song Y 2017 The gut microbiome of hooded cranes (Grus monacha ) wintering at Shengjin Lake, China MicrobiologyOpen 6 e00447 10.1002/mbo3.447