自由論題［投稿論文：研究論文］

DNA Metabarcoding Analysis of LongEared Owl Asio otus Pellets Reveals
Small Animals as Its Prey
DNA メタバーコーディング解析が可能にした
トラフズク Asio otus のペリットにおける小型餌動物の検出

Takumi Shimizu

Doctoral Program, Graduate School of Media and Governance, Keio University

清水 拓海
慶應義塾大学大学院政策・メディア研究科後期博士課程
Correspondence to: takuandk.m@gmail.com

Haruki Natsukawa

Japan Society for the Promotion of Science Overseas Fellow

夏川 遼生
日本学術振興会海外特別研究員

Hiroki Yuasa

Doctoral Program, Graduate School of Media and Governance, Keio University
湯浅 拓輝
慶應義塾大学大学院政策・メディア研究科後期博士課程

Hiroki Kuroda

Professor, Faculty of Environment and Information Studies, Keio University

黒田 裕樹
慶應義塾大学環境情報学部教授

Tomohiro Ichinose

Professor, Faculty of Environment and Information Studies, Keio University

一ノ瀬 友博慶應義塾大学環境情報学部教授

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DNA Metabarcoding Analysis of Long-Eared Owl Asio otus Pellets Reveals Small Animals as Its Prey

Abstract:

The feeding habits of apex predators such as raptors have a major influenceon the local ecosystem, but their predation targets have been analyzed by visualobservation that requires extremely proficient skills of taxonomic classification to
identify small animals. Identifying prey animals at the species level reveals predator
biology as well as important information for conserving predators, but it is difficult
using conventional techniques. In this study, we aimed to clarify the diet of the longeared owl Asio otus by DNA metabarcoding of its pellets in the central region of
Kanagawa Prefecture in Japan, using three types of universal primer sets. The results
indicate that the long-eared owl feeds on various types of warm-blooded animals
including birds, rodents and bats in winter. Our findings also demonstrate the highefficiency and reliability of DNA metabarcoding in the study of predator–prey
relationship.
猛禽類などの頂点捕食者の餌となる動物を種レベルで同定することは捕食者の生態を明らかにし、保全するために重要な情報となる。しかし、餌動物を特定するためには目視を主流とした高度な分類学的知識などが必要とされる。
そこで、本研究では分子生物学的手法によって簡易的に餌動物を特定することにした。３種類のユニバーサルプライマーを用いて神奈川県中部に生息するトラフズク Asio otus のペリットを DNA メタバーコーディング手法によって解析した。その結果、トラフズクは冬季に小鳥や齧歯類、コウモリなど様々な
小型の恒温動物を捕食していることが明らかとなった。捕食者と被食者の関係を研究するにあたって DNA メタバーコーディングが高効率で信頼性の高い手法であることが再確認されたと言える。

Keywords: diet, metabarcoding, universal primer

食性、メタバーコーディング、ユニバーサルプライマー

1

INTRODUCTION
Information regarding predators such as their niche, distribution, and community

in the ecosystem is important for revealing their potential prey. In particular, Apex
predators, also called as alpha predators or top predators, reign supreme in the foodchain, and their top-down control of mesopredators and herbivores significantly
inﬂuences the local predator–prey interactions (Estes et al., 2011).
Several studies have been performed on the prey species of raptors based on
visual observations such as the pellet (the undigested material that raptor spit out iscalled pellet) analysis (Korpimäki, 1985), stomach content analysis (Tomback, 1975),
direct behavior observations (Meyer et al., 2004), and video monitoring of nests
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自由論題

(McPherson et al., 2016). In the case of owl species, the pellet analysis has beencommonly used because owls are nocturnal animals, occupying a wide range offorest areas (Glading et al., 1943). However, this method requires enough caution to
avoid oversight and overestimation of prey species. Raptors usually tear their preyapart as they feed, and several parts and bones of the prey are digested by the gastricjuice; hence, morphological identification of prey animals after digestion requires ahigh level of exclusive knowledge and experience. The identification of prey animals
and the elucidation of prey selectivity strongly depend on the accuracy ofexperimental approach. The more accurate the identification of prey species, thebetter the elucidation of local predator–prey relationship (Hardy et al., 2010).
DNA metabarcoding (method for detecting organisms based on DNA
information contained in a sample) can overcome the limitations associated withconventional methods and potentially be a powerful method to enable theidentification of prey to the species level (Sullins et al., 2018). With the application ofthis method for diet analysis, significant information can be obtained to elucidate
food web trophic structure (Pompanon et al., 2012). The application of DNA
metabarcoding to diet identification improves the precision of analysis. Moreover, it
does not require high level of knowledge and experience, leading to novel findings
and reconfirmation of predator–prey relationships. In addition, this method canprovide a useful framework for the study of prey species, especially for researchers
who do not have enough experience as morphologists.
Pellets of the long-eared owl, Asio otus, also known as the northern long-earedowl, distributed in the Holarctic Region such as Europe and North America, havebeen thoroughly analyzed in some countries (Tome, 1994; Birrer, 2009). However,there are few prey studies about long-eared owls in Asian areas like Japan (Chiba etal., 2005) and China (Zhao et al., 2011). In addition, most of these studies employedvisual observation, and therefore further in-depth analysis using new technologies
such as DNA metabarcoding is worth conducting. In fact, there have been reports ofpellet analysis showing a great variety of prey species, although the long-eared owl isthought to feed mainly on rodents (Gryz and Krauze-Gryz, 2015). In this study, we

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DNA Metabarcoding Analysis of Long-Eared Owl Asio otus Pellets Reveals Small Animals as Its Prey

aimed to clarify the diet of long-eared owl by DNA metabarcoding of its pellets. We
also aimed to elucidate the reliability and future application potential of DNA
metabarcoding.

2

MATREIALS AND METHODS
From the collected samples, randomly selecting ten pellets, bones of length 1 cm

or more were removed, and the remaining residue was used for DNA extraction,using the NucleoSpin Plant II Maxi Kit (U0772A; TaKaRa, Shiga, Japan). In the firstpolymerase chain reaction (PCR), a portion of the mitochondrial COI (cytochromeoxidase subunit I) region of the COI primer set, mitochondrial 12S rRNA region of
the MiMammal primer set, and mitochondrial 16S rRNA region of the gBird primer
set were amplified using the following primers: 5´-GGWACWGGWTGAACWGTWTAYCCYCC-3´ (IntF) and 5´-TAHACTTCNGGGTGKCCRAARAATCA-3´(HCOmR) for COI (Folmer et al., 1994); 5´-NNNNNNGGGTTGGTAAATTTCGTGCCAGC-3´ (MiMammal-U-F) and 5´-NNNNNNCATAGTGGGGTATCTAATC
CCAGTTTG-3´ (MiMammal-U-R), 5´-NNNNNNGGACTGGTCAATTTCGTG
CCAGC-3´ (MiMammal-E-F) and 5´-NNNNNNCATAGTGAGGTATCTAATCTCAGTTTG-3´ (MiMammal-E-R), 5´-NNNNNNGGGTTGGTTAATTTCGTGCC
AGC-3´ (MiMammal-B-F) and 5´-NNNNNNCATAGTGGGGTATCTAATCCCA
G T T T G - 3´ ( M i M a m m a l - B - R ) f o r M i M a m m a l ( U s h i o e t a l ., 2 017 );5 ´ - N N N N N N C A A G T AT T G A A G G T G AT G - 3 ´ ( g B i r d F ) a n d
5´-NNNNNNCCCTGGGGTAGCTTGG-3´ (gBirdR) for gBird (Seibutugiken Co.,
Ltd.). The forward primers (IntF, MiMammal-U-F, MiMammal-E-F, MiMammalB-F and gBirdF) included the adapter sequence 5´-ACACTCTTTCCCTACACGACGCTCTTCCGATCT-3´ before the above region-specific sequences, and the reverse
primers (HCOmR, MiMammal-U-R, MiMammal-E-R, MiMammal-B-R and gBirdR)
included the adapter sequence 5´-GTGACTGGAGTTCAGACGTGTGCTCTTCCG
ATCT-3´ before the above sequences. DNA library was prepared with each primer
set using the two-step tailed PCR method (Miya et al., 2015). The target amplicons
were subjected to MiSeq sequencing using the 600-cycle MiSeq Reagent Nano Kit
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v3 (MS-102-3003; Illumina, San Diego, California). To determine the species identity
based on the sequences obtained by MiSeq, the data were processed using FASTQ
Barcode Splitter, which is a component of FASTX Toolkit. We only extracted
sequences with the readings that exactly matched the primers used. The primer
sequences were deleted from the read sequences obtained from MiSeq analysis, andthen sequences with the quality value of less than 20 were removed. The sequencesthat had 40 bases or less were discarded with its pair sequence using the Sickle tool.
High-quality pair reads were combined using FLASH tool, and OTU (operationaltaxonomic units) clustering was performed using USEARCH with the binding
sequence. The sequence reads that had more than 97% homology were classified, theremaining OTUs were subjected to a BLAST search against the nr database, andlineage estimation was performed. Non-dietary items (e.g., Large mammalian,
Bacteria, and Protists) and those with low taxonomic resolution (e.g., Eukaryota)
were discarded.

3

RESULTS
The pellets for DNA metabarcoding analysis were collected almost every day

from mid-February to mid-March, 2018. The monitoring point of the long-earedowls, that is, an overwintering tree, is located in the Central Kanagawa Prefecture in
Japan and is surrounded by cropland, grassland, industrial and commercial
installations, and urban residential areas (Fig 1). To prevent DNA contamination of
the human body and surrounding organisms at the sampling site, we laid a vinyl sheet
under the overwintering tree and collected the pellets of long-eared owls wearing
gloves. Overall, 40 pellet samples were collected from the vinyl sheet laid under the
overwintering tree. The recovered pellets were immediately placed in a plastic bag
and frozen.
Based on the results of DNA metabarcoding of pellets of the long-eared owl, we
obtained 127763 sequencing reads by MiSeq analysis, which contained 42834,
60419, and 24510 reads, using the sequences of the COI, Mimammal and gBird
primer sets, respectively. Further classification of these reads to the species level340

DNA Metabarcoding Analysis of Long-Eared Owl Asio otus Pellets Reveals Small Animals as Its Prey

Figure 1 Map of the study area. Roost of the long-eared owl Asio otus is marked as a black
point. Land use around the roost is illustrated. The Sagami River is in the vicinity. (HighResolution Land Use and Land Cover Map of Japan. ver.18.03)

showed seven birds and two mammals (Table 1).
The species obtained for each primer were as follows. Six birds (Common
Kingfisher Alcedo atthis, long-eared owl, Meadow Bunting Emberiza cioides,
Brown-eared Bulbul Hypsipetes amaurotis, Eurasian Tree Sparrow Passer montanus,and Dusky Thrush Turdus eunomus) and two mammals (Japanese House Bat
Pipistrellus abramus and House Mouse Mus musculus) were identified using the COI
primer sets. Three birds (Eurasian Tree Sparrow, long-eared owl and Meadow
Bunting) and two mammals (Japanese House Bat and House Mouse) were identified
using the Mimammal primer sets. Five small birds (Eurasian Tree Sparrow, Dusky
Thrush, Common Kingfisher, Meadow Bunting and Malagasy Bulbuls H.
madagascariensis) were identified using the gBird primer sets.

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Table 1 List of species detected from the pellets of long-eared owl Asio otus by DNA
metabarcoding using each universal primer. Sequence reads and identity of the detected species
are described.

Primer name
CO1

Aves

Mammalia

Mimammal

Aves

Mammalia

gBird

4

Aves

Reads

Species

Identity

9 206
7 195
2 836
1 010
365
160

Alcedo atthis
Asio otus
Passer montanus
Turdus eunomus
Emberiza cioides
Hypsipetes amaurotis

100%
100%
100%
99.4%
100%
100%

4 037
2 251

Pipistrellus abramus
Mus musculus

100%
100%

2 857
321
21

Passer montanus
Asio otus
Emberiza cioides

100%
99.5%
100%

1 541
1 278

Pipistrellus abramus
Mus musculus

100%
100%

16 687
7 421
128
108
89

Passer montanus
Turdus eunomus
Alcedo atthis
Emberiza cioides
Hypsipetes madagascariensis

100%
99.7%
99.7%
100%
98%

DISCUSSION
DNA metabarcoding is commonly used for environmental DNA analysis todetect amphibians and fish (Miya et al., 2015; Valentini et al., 2016; Bálint et al.,2018). In addition, diet analysis by DNA metabarcoding has been used for assessing

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DNA Metabarcoding Analysis of Long-Eared Owl Asio otus Pellets Reveals Small Animals as Its Prey

feeding preferences and population structure of vampire bats using blood meal andfaucal samples (Bohmann et al., 2018) and for illustrating the dietary compositions ofshorebird as well as generalist grasshopper, which revealed their diet demands fortheir survival and possible conservation (Huang et al., 2022; Yamamoto and Uchida,2018). In this study, we conducted a diet analysis of the long-eared owl during thewintering period in Japan by DNA metabarcoding of its pellets. The results helped us
identify a small bat (Japanese House Bat) and birds (Common Kingfisher, Meadow
Bunting, Brown-eared Bulbul, Eurasian Tree Sparrow and Dusky Thrush), which areusually difficult to identify by morphological classification. These results suggest
that, compared with those by conventional methods, this method can greatly reduce
total eﬀort and expense of the analysis.
Based on the results, we identified that the Malagasy Bulbuls, a close relative
species of Brown-eared Bulbul, as the Brown-eared Bulbul is not registered in thesequence amplified by the gBird primer set. A species closely related to Malagasy
Bulbuls might have been detected. We thought that the remaining seven species
identified were reliable, namely, five small birds (Common Kingfisher, Meadow
Bunting, Brown-eared Bulbul, Eurasian Tree Sparrow and Dusky Thrush) and two
mammals (Japanese House Bat and House Mouse). All of them have been reported toinhabit the area of the monitoring point of this study (Survey of Samukawa town
Animal and Plants 2016). The present study results directly indicated that relationshipexisted between these seven animals hunted by the long-eared owls. The long-eared
owl is thought to ﬂy around the range of approximately 969 ha near overwintering
trees (Emin et al., 2018), and their winter food composition in Northern Turkey
mainly comprises small rodents such as voles (Ahmet et al., 2017). As voles are notreported to inhabit the area around the monitoring point, the owls may instead catchhouse mouse and other small animals, although the predominant species among them
are still unknown because we did not perform quantitative analysis in this study.
In the previous research in China and Japan, it is reported that the long-earedowls are preying on Japanese House Bat in urban areas, and therefore the results ofthis research reconfirm it (Chiba et al., 2005; Tian et al., 2015). There are few studies
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in Asia that identified small birds at the species level, which the long-eared owls preyon, so the results of this study indicating that the long-eared owls comprehensive
prey on small birds may be very significant.
In DNA metabarcoding, the quality of DNA contained in pellets is one of themost important factors to obtain good results. Several factors such as bacteria andfungi in pellets and exposure to ultraviolet rays or rain might significantly damage
the DNA (Oehm et al., 2011). In this study, five fungal species were detected as
contaminants, although we collected pellets almost every day to maintain fresh
condition. One possibility for these contaminations is that fungal DNA is originally
included in pellets. Frequently, raptors prey on small mammals and birds, and hence,
there is a possibility that the fungi on these prey animals can be detected in pellets(Ciesielska et al., 2017). Another possibility is that fungi, which originally exist on
vinyl sheet, simply adhere to pellets. In studies targeting animals living under wildconditions, it is difficult to avoid these contaminations, but we recommend the use ofwell-sterilized vinyl sheets in future studies.
In this study, all seven potential prey animals of the long-eared owl weredetected using the COI primer set. The Mimammal primer set detected both prey
mammals and the gBird primer set detected all five prey avians (assuming H.
madagascariensis as H. amaurotis). In the future, prey animals can be efficiently
detected using the COI primer set with the most comprehensive database (Andujar etal., 2018) in the first step and running analysis using suitable universal primers in thesecond step. On the other hand, the high sensitivity of DNA metabarcoding methods
may produce abundant false positives as a consequence of, for example, secondary
predation or contamination from any source (Sheppard et al., 2005). However, infood habitat analysis of large carnivores such as raptors, these restrictions can be
dealt with by considering the biota of the survey site and the ecology of the target
species.

5

CONCLUSION
This study demonstrates that DNA metabarcoding is a suitable method to obtain344

DNA Metabarcoding Analysis of Long-Eared Owl Asio otus Pellets Reveals Small Animals as Its Prey

fundamental information about small prey animals using pellets without requiringexpert knowledge and complicated technique. In the future, the combination of DNA
metabarcoding and observational data will allow researchers to obtain a great amountof reliable and accurate information on predator–prey relationships. The method
described in this study can be applied for the prey analysis of other species, and it istremendously eﬀective for listing prey animals. DNA metabarcoding using multiple
universal primers is highly likely to be the mainstream technique of prey animal
analysis in the future.
ACKNOWLEDGEMENTS
We thank Takashi Shiokawa for information on the long-eared owl. In addition, this study
was supported by JSPS KAKENHI (Grant number 16K08131).

REFERENCES
Ahmet, Y. S., Kemal, B., Haluk, K. (2017) “Comparison of winter diet of long-eared owls Asiootus (L., 1758) and short-eared owls Asio flammeus (Pontoppidan, 1763) (Aves: Strigidae)
in Northern Turkey”, Acta Zoologica Bulgarica. 69, pp. 345-348.
Andujar, C., Arribas, P., Yu, D. W., Vogler, A. P., Emerson. B. C. (2018) “Why the COI barcode
should be the community DNA metabarcode for the metazoa”, Molecular Ecology. 27, pp.
3968-3975.
Bálint, M., Nowak, C., Márton, O., Pauls, US., Wittwer, C., et al. (2018) “Accuracy, limitations
and cost efficiency of eDNA-based community survey in tropical frogs”, Molecular
Ecology Resources. 18, pp. 1415-1426.
Birrer, S. (2009) “Synthesis of 312 studies on the Diet of the long-eared owl Asio otus”, Ardea.
97, pp. 615-624.
Bohmann, K., Gopalakrishnan, S., Nielsen, M., Nielsen, L. D. S. B., Jones, G., et al. (2018)“Using DNA metabarcoding for simultaneous inference of common vampire bat diet andpopulation structure”, Molecular Ecology Resources. 18(5), pp. 1050-1063.
Chiba, A., Onojima, M., Kinoshita, T. (2005) “Prey of the long-eared owl Asio otus in thesuburbs of Niigata City, central Japan, as revealed by pellet analysis”, Ornithological
Science. 4, pp. 169-172.
Ciesielska, A., Kornillowicz-Kowalska, T., Kitowski, I., Bohacz, J. (2017) “The dispersal ofrodent-borne strains of Aphanoascus keratinophilus and Chrysosporium tropicum bypellets of predatory birds”, Avian Biology Research. 10, pp. 218-230.
Emin, D., Toxopeus, G. A., Groen, A. T., Kontogeorgos, I., Georgopoulou, E., Xirouchakis, S.
(2018) “Home range and habitat selection of long-eared Owls (Asio otus) in Mediterranean
agricultural landscape (Crete, Greece)”, Avian Biology Research. 11, pp. 204-218.
Estes, A. J., Terborgh, J., Brashares, S. J., Power, E. M., Berger, J., et al. (2011) “Trophic

KEIO SFC JOURNAL Vol.22 No.2 2022

345

自由論題
downgrading of planet Earth”, Science. 333, pp. 301-306.
Folmer, O., Black, M., Hoeh, W., Lutz, R., Vrigenhoek, R. (1994) “DNA primers for
amplification of mitochondrial cytochrome c oxidase subunit I from diverse metazoan
invertebrates”, Molecular Marine Biology and Biotechnology. 3, pp. 294-299.
Glading, B., Tillotson, D. F., Selleck, D. M. (1943) “Raptor pellets as indicators of food habits”,
California Fish and Game. 29, pp. 92-121.
Gryz, J., Krauze-Gryz, D. (2015) “Seasonal variability in the diet of the long-eared owl Asiootus in a mosaic of field and forest habitats in central Poland”, Acta Zoologica
Cracoviensia. 58, pp. 173-180.
Hardy, C. M., Krull, E. S., Hartley, D. M., Oliver, R. L. (2010) “Carbon source accounting forfish using combined DNA and stable isotope analyses in a regulated lowland river weirpool”, Molecular Ecology. 19, pp. 197-212.
Huang, P-Y., Poon, E. S. K., Chan, L. Y., Chan, D. T. C., Huynh, S., et al. (2022) “Dietary
diversity of multiple shorebird species in an Asian subtropical wetland unveiled by DNA
metabarcoding”, Environmental DNA. 4, pp. 1381-1396.
Korpimäki, E. (1985) “Diet of the Kestrel Falco tinnunculus in the breeding season”, Ornis
Fennica. 62, pp. 130-137.
McPherson, S. C., Brown, M., Downs, C. T. (2016) “Diet of the crowned eagle (Stephanoaetus
coronatus) in an urban landscape: potential for human-wildlife conflict?”, Urban
Ecosystems. 19, pp. 383-396.
Meyer, K. D., McGehee, S. M., Collopy, M. H. (2004) “Food deliveries at swallow-tailed kite
nests in southern Florida”, The Condor. 106, pp. 171-176.
Miya, M., Sato, Y., Fukunaga, T., Sado, T., Poulsen, J. Y., Sato, K., et al. (2015) “MiFish, a set ofuniversal PCR primers for metabarcoding environmental DNA from fishes: detection of
more than 230 subtropical marine species”, Royal Society Open Science. 2, 150088.
Oehm, J., Juen, A., Nagiller, K., Neuhauser, S., Traugott, M. (2011) “Molecular scatology: how
to improve prey DNA detection success in avian faeces?”, Molecular Ecology Resources.
11, pp. 620-628.
Pompanon, F., Deagle, B. E., Symondson, W. O., Brown, D. S., Jarman, S. N., Taberlet, P. (2012)“Who is eating what: diet assessment using next generation sequencing”, Molecular
Ecology. 21, pp. 1931-1950.
Samukawa town office. (2016) “Survey of Samukawa city Animal and Plants”
Sheppard, S. K., Bell, J., Sunderland, K. D., Fenlon, J., Skervin, D., Symondson, W. O. C.
(2005) “Detection of secondary predation by PCR analyses of the gut contents ofinvertebrate generalist predators”, Molecular Ecology. 14, pp. 4461-4468.
Sullins, D. S., Haukos, D. A., Craine, J. M., Lautenbach, J. M., Robinson, S. G., et al. (2018)“Identifying the diet of a declining prairie grouse using DNA metabarcoding”, The Auk.
135, pp. 583-608.
Tian, L., Zhou, X., Shi, Y., Guo, Y., Bao, W. (2015) “Bats as the main prey of wintering long ‐eared owl (Asio otus) in Beijing: Integrating biodiversity protection and urban
management”, Integrative Zoology. 10, pp. 216-226.
Tomback, D. F. (1975) “An emetic technique to investigate food preferences”, The Auk. 92, pp.
581-583.
Tome, D. (1994) “Diet composition of the long-eared owl in central Slovenia: seasonal variationin prey use”, Journal of Raptor Research. 28, pp. 253-258.
Ushio, M., Fukuda, H., Inoue, T., Makoto, K., Kishida, O., et al. (2017) “Environmental DNA
enables detection of terrestrial mammals from forest pond water”, Molecular Ecology

346

DNA Metabarcoding Analysis of Long-Eared Owl Asio otus Pellets Reveals Small Animals as Its Prey
Resources. 17, pp. 63-75.
Valentini, A., Taberlet, P., Miaud, C., Civade, R., Herder, J., et al. (2016) “Next-generation
monitoring of aquatic biodiversity using environmental DNA metabarcoding”, Molecular
Ecology. 25, pp. 929-942.
Yamamoto, S., Uchida, K. (2018) “A generalist herbivore requires a wide array of plant species
to maintain its populations”, Biological Conservation. 228, pp. 167-174.
Zhao, W., Shao, M., Song, S., Liu, N. (2011) “Niche separation of two sympatric owls in thedesert of northwestern China”, Journal of Raptor Research. 45, pp. 174-179.
〔受付日 2022. 7. 10〕〔採録日 2022. 11. 6〕

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