Philippine Journal of Science 150 (2): 545-555, April 2021 ISSN 0031 - 7683 Date Received: 17 Sep 2020

Pilot Fecal DNA Barcoding on Selected Fruit in Davao City, Philippines

Michael G. Bacus2, Sammer C. Burgos1, Hannah G. Elizagaque1, Kameela Monique A. Malbog1, Mae A. Responte1,3, Lief Erikson D. Gamalo1,2,3, Marion John Michael M. Achondo1,3, and Lyre Anni E. Murao1,2,3*

1Department of Biological Sciences and Environmental Studies 2Philippine Genome Center Mindanao 3Wildlife-Human Interaction Studies, Ecological Research and Biodiversity Conservation Laboratory University of the Philippines Mindanao, Mintal Davao City, Region XI 8000 Philippines

The “Species from Feces” DNA barcoding offers new opportunities to study the challenging and systematics of Philippine bats using a minimally-invasive strategy that employs a short 200- bp mitochondrial encoded cytochrome c oxidase I (mt COI) sequence. A pilot application of the technique to five species of fruit bats collected from Davao City, Philippines revealed accurate species identification and the extended ability to assess genetic diversity and evolutionary relationships. The 95–100% sequence identity matched with the field identification of bats, including the endemic Ptenochirus jagori, although only 62% of the samples could be sequenced. A decreasing trend in genetic diversity was noted from widespread species such as amplexicaudatus, brachyotis, and minimus to species with limited geographic distribution (e .g . P . jagori) or possible recent colonization (e .g . spelaea). Genetic diversity, principal coordinate analysis (PCoA), and phylogenetic analysis also showed distinct genetic lineages of C . brachyotis, R . amplexicaudatus, and M . minimus from their conspecifics outside the Philippines, while E . spelaea and the endemic P . jagori exhibited genetic homogeneity. The findings on genetic diversity and relationships were consistent with previous studies using longer COI segment or other biomarkers. In conclusion, the Species from Feces DNA barcoding presents a minimally invasive and pragmatic approach to explore bat assemblages with the additional utility to examine genetic structures and relationships, which may be used to support studies on diversity, evolution, and biogeography, thereby rapidly facilitate conservation initiatives.

Keywords: evolution, fecal barcoding, fruit bats, genetic diversity

INTRODUCTION 2018; Heaney et al. 2005; Ingle and Heaney 1992). Among these species, 32% are estimated to be under the family Bats (Order: Chiroptera) are one of the most diverse and Pteropodidae, which are the fruit- or nectar-feeding bats widely distributed groups of . Around 1,386 (Tanalgo and Hughes 2018). Although members of this species of bats exist around the world, of which around family share some unique ecological features (e.g. only 70 species are present in the Philippines (Burgin et al. eat plant matter, most do not echolocate), they differ *Corresponding Author: [email protected] from each other in terms of habitat preference, roosting

545 Philippine Journal of Science Bacus et al.: Fecal DNA Barcoding on Selected Vol. 150 No. 2, April 2021 Philippine Fruit Bats habits, and aggregation sizes (Heaney et al. 2016). Some between conspecifics, thus making it an efficient tool for genera of the family are also endemic in the country (e.g. species identification (Hebert et al. 2003). Analysis of 165 Haplonycteris and Ptenochirus), which is an evidence bat species in Southeast Asia revealed that DNA barcoding of the rich and enormous evolutionary diversification of using the mt COI gene could effectively discriminate bats within the archipelago (Heaney et al. 2005; Heaney between morphologically or acoustically distinct et al. 2016). species, except for some closely related species such as Macroglossus minimus (É. Geoffroy Saint-Hilaire, 1810) Bats provide numerous ecosystem services such as vs. Macroglossus sobrinus K. Andersen, 1911, Cynopterus pollination, seed dispersal, and pest suppression (Kunz et horsfieldii Gray, 1843 vs. Cynopterus brachyotis Müller, al. 2011). They are also indicators for biodiversity due to 1838, Rhinolophus macrotis Blyth, 1844 vs. Rhinolophus their critical role in maintaining ecosystem health (Jones et siamensis Gyldenstolpe, 1917, and Myotis annamiticus al. 2009). These underscore the importance of monitoring Kruskop and Tsytsulina, 2001 vs. Myotis laniger Peters, bat populations to yield appropriate management decisions 1871 (Francis et al. 2010). and strategies for chiropteran conservation (Russo and Voigt 2016). However, the first taxonomic key of bats Non-invasive approaches for obtaining genetic samples in the Philippines that was developed in 1992 has not are safer for bats and make genetic techniques more been updated since then, resulting in huge gaps in the accessible to researchers. Non-lethal strategies to obtain establishment of definitive taxonomic and systematics bat DNA include hair and wing punches (Pfunder et records in the Philippines (Tanalgo and Hughes 2018). al. 2004). Recently, a DNA mini-barcode assay called Species from Feces was developed for bat identification Bat identification is typically based on morphological from guano or fecal pellets obtained from abandoned traits, which often requires capturing bats manually mines used by bats in Arizona, Colorado, New Mexico, or through traps (i.e. mist nets, harp nets, etc.). Due to and Utah in the United States of America (USA) using their small size, morphological identification demands a 202-bp segment, which overlaps with the standard careful examination and occasional misidentification ~ 500-bp barcode from the mt COI-5P region used may occur (Francis 1989; Francis et al. 2010). This is in the Barcode of Life Database or BOLD (Walker further complicated by sympatric and morphologically et al. 2016). Evaluation of the assay in tissues and similar species, which may be difficult to distinguish feces of 54 chiropteran species from eight bat families (Lim et al. 2017). In many cases, confirmation requires (Pteropodidae, Rhinolophidae, Rhinopomatidae, morphometric analysis of the skull and dentition with Molossidae, Mormoopidae, Noctilionidae, reference to published materials (Francis et al. 2010) Phyllostomidae, and Vespertilionidae) validated its and through acoustic devices (Russo and Voigt 2016). effectiveness to discriminate between species. The assay Hence, identification of bats in the field can be extremely was also confirmed to be bat-specific since arthropod challenging while collection of voucher specimens is prey was not detected using next-generation sequencing delimited by government and ethical restrictions (Wilson platforms. Although the assay has been recommended et al. 2014). for individual (single feces) or community (guano or DNA barcoding has an important application for pooled feces) analysis of bat populations, its utility in conservation as proper inventory of species is critical for Philippine bats has not been demonstrated. This study is assigning the appropriate units and scales in conservation a pilot demonstration of minimally invasive molecular planning (Francis et al. 2010). DNA barcode markers can profiling of selected Philippine fruit bats from Davao also be used to extract information on genetic diversity City using fecal matter based on the mt COI gene. and relatedness of populations, and even discover new species for the purposes of conservation planning (Francis et al. 2010; Wilson et al. 2014). Additional strategies with a more comprehensive approach for barcoding are MATERIALS AND METHODS needed for a concise and robust distinction of population relatedness and genetic structure. Sampling Two sampling sites in Davao City, Philippines were DNA barcoding has been recently introduced as another selected for this study – Mintal (7.0854° N, 125.4864° approach to bat identification, with the mt COI gene as E) and Malagos (7.1876° N, 125.4289° E). Sampling was the most commonly used marker to distinguish between conducted at 18:00–5:00 for five days in May–July 2017 species as has been demonstrated for 20 bat species in and two days in November 2018 for Mintal and Malagos, the Phyllostomidae family and 19 bat species in the respectively. Bats were collected through convenience Pteropodidae family (Hernandez-Davila et al. 2012; sampling using mist nets, and the morphometric Luczon et al. 2019). Its sequence is also conserved characteristics were measured such as total length,

546 Philippine Journal of Science Bacus et al.: Fecal DNA Barcoding on Selected Vol. 150 No. 2, April 2021 Philippine Fruit Bats forearm length, tail length, and ear length. A preliminary Sequence Analysis identification was given according to their morphometric The sequences were cleaned and edited using FinchTV characteristics using the taxonomic key developed by software (Geospiza, Inc.) and a contig sequence was Ingle and Heaney (1992) (Appendix Table I). Bats were generated from the forward and reverse sequences temporarily placed in clean muslin bags until defecation using BioEdit (Ibis Biosciences, California, USA) (Hall and were released after a maximum possible amount of 1999). The Basic Local Alignment Search Tool (BLAST) fecal sample was collected. In Malagos, non-endemic from NCBI (http://www.ncbi.nlm.nih.gov/) and BOLD and non-threatened species were anesthetized through (biodiversitygenomics.net/projects/bold) were used for intraperitoneal injection of tiletamine-zolazepam and distance analysis with 22 total sequences for Rousettus sacrificed by cardiac exsanguination. A total of 29 bat leschenaultii (Desmarest, 1820), 24 for Rousettus fecal samples were collected from both sampling sites, amplexicaudatus (É. Geoffroy Saint-Hilaire, 1810) (14 either after bat defecation, or directly collected from from the Philippines), 16 for Ptenochirus jagori (Peters, bat intestines following bat dissection. Ear voucher 1861) (all from the Philippines), three for Ptenochirus specimens were collected from one individual per minor (Yoshiyuki, 1979), 30 for Macroglossus sobrinus, species. Samples were maintained on ice while on the 45 for Macroglossus minimus (nine from the Philippines), field and immediately transferred to –80 °C for long- 27 for Eonycteris spelaea (Dobson, 1871) (six from the term storage. Philippines), 12 for Eonycteris robusta Miller, 1913 (all from the Philippines), 40 for Cynopterus brachyotis (21 This study was approved by the Department of from the Philippines), and 19 for Cynopterus sphinx (Vahl, Environment and Natural Resources – Region XI (Wildlife 1797). Contig sequences were aligned with reference Gratuitous Permit No. XI-2017-05 and No. XI-2018-07) sequences from BOLD using the MUSCLE algorithm in and by the Institutional Care and Use Committee MEGA 7 software (Kumar et al. 2016). The alignment of the University of the Philippines Manila (Protocol No.: was trimmed on both ends and gaps were deleted to 2018-109). generate a complete alignment of approximately 200 base pairs. Pairwise distance analysis of all bat sequences DNA Extraction, Polymerase Chain Reaction, and from the Philippines and mean diversity analysis per bat Sequencing species were conducted using the Maximum Composite Fecal samples were subjected to total DNA extraction Likelihood model (Tamura et al. 2004). Codon positions using the NucleoSpin DNA Stool Kit (Macherey-Nagel included were 1st+2nd+3rd+Noncoding. PCoA was also GmbH & Co., Germany) and tissues were subjected performed for species delineation using the pairwise to total DNA extraction using the DNeasy Blood & distance matrix of all bat sequences using Past3 software Tissue Kit (Qiagen, Hilden, Germany) according to the (Hammer et al. 2001). manufacturer’s instructions. The quality of the DNA extracts was initially assessed via electrophoresis using The outgroup taxon used for phylogenetic analysis a 1% agarose gel. All DNA samples were subjected to was helvum (Kerr, 1792), which is an African polymerase chain reaction (PCR) using the 2X Taq Master fruit bat divergent to Asian pteropodids but shares a Mix (Vivantis, Subang Jaya, Malaysia) using the primer recent common ancestor with all other fruit bats. The pair SFF_145f and SFF_351r (Walker et al. 2016). A total jModelTest v.2.1.10 software was used to calculate for of 5 μL 2X Taq Master Mix was combined with 0.3-mM the best phylogenetic model for the five bat taxa using the Bayesian Information Criterion (BIC) (Posada 2008). MgCl2 (1 μL/reaction), 0.4-μM Primer SFF_145f (1 μL/ reaction), 0.4-μM Primer SFF_351r (1 μL/reaction), Phylogenetic analysis was performed using the best model and 2-μL DNA from the bat tissue or feces. The PCR available in BEAST v.1.10.4 (HKY+G) with a length of conditions were as follows: 2 min at 94 °C; 35 cycles chain of 50 million iterations (Suchard et al. 2018). The of 30 s at 94 °C, 30 s at 60 °C, and 30 s at 72 °C; and 5 rest of the run parameters were set to the default value. min at 72 °C. A total of 4 μL from the PCR product was All transition kernels or operators were inspected, and re-amplified through chain PCR using double volume of none had an acceptance rate of zero. Tracer v.1.7.1 was the aforementioned reagents. PCR products were checked used to summarize the resulting parameter estimates through 1.5% agarose gel electrophoresis and bands of the (Rambaut et al. 2018). The traces of all parameters as expected size (202 bp) were extracted using the GF-1 Gel well as the estimated sampling size of each continuous DNA Recovery Kit (Vivantis Technologies Sdn. Bhd., parameter were examined to determine whether the results Subang Jaya, Malaysia) according to the manufacturer’s are sufficient to terminate the analysis. A maximum clade instructions. Gel-extracted samples were sent to Macrogen credibility tree was generated using the TreeAnnotator Inc. Korea for sequencing. v.1.10.4, and the resulting phylogenetic tree was visualized using FigTree v.1.4.4 (http://tree.bio.ed.ac.uk/software/ figtree).

547 Philippine Journal of Science Bacus et al.: Fecal DNA Barcoding on Selected Vol. 150 No. 2, April 2021 Philippine Fruit Bats

RESULTS Molecular Identification of Fruit Bats The generated sequences from fecal matter and the corresponding ear voucher specimen (Table 1) exhibited Effectiveness of Fecal Barcoding in Selected Bats 94–100% identity (Table 2). Distance analysis of fecal A total of 29 fecal samples from fruit- and nectar-feeding sequences using the BOLD database resulted in 95–100% bats in Davao City, Philippines – consisting of five species intraspecific identity that matched exactly with the morphologically identified as Cynopterus brachyotis, morphological identification (Table 2). Nearest neighbor Rousettus amplexicaudatus, Macroglossus minimus, analysis of the obtained sequences with available mt COI Ptenochirus jagori, and Eonycteris spelaea (Appendix sequences from Philippine bats also resulted in a consistent Figure I) – were subjected to DNA barcoding. DNA extracts match between the field and molecular-based species obtained from all fecal samples yielded no visible bands after identification, with intraspecific nearest neighbor distances electrophoresis visualization using a 1% agarose gel (data not of 0–0.04 or up to 4% difference in sequences (Table 2). shown), indicating either fecal DNA levels below detection threshold or poor quality of the DNA extracts. Nevertheless, Individual comparisons were made between the voucher the 202-bp mt CO1 was PCR amplified from fecal matter specimens and bats from the Philippines and outside the in 78–100% of the samples per species, with an overall rate country. Within a taxon, the bats in this study and from of 83% (24 out of 29 samples) successful amplification various parts of the Philippines had a high average identity (Table 1). However, sequences were generated for only of 94–99% with reference to the voucher specimen (Figure 62% of the batch (18 out of 29 samples) due to poor quality 1A). The voucher specimens of Philippine M. minimus chromatograms obtained for selected samples.

Table 1. Molecular tests on fecal samples from morphologically identified fruit bats in Davao City, Philippines. BOLD accession nos. No. of sam- mt COI amplification Sequence obtained Morphological ID ples tested (% of samples) (% of samples) Fecal samples Ear voucher specimen Cynopterus brachyotis 14 11 (78.6) 7 (50.0) UPMIN005-19 UPMIN022-19 UPMIN006-19 UPMIN008-19 UPMIN013-19 UPMIN016-19 UPMIN018-19 UPMIN019-19

Rousettus amplexicau- 7 6 (85.7) 5 (71.4) UPMIN003-19 UPMIN002-19 datus UPMIN004-19 UPMIN003-19 UPMIN010-19 UPMIN011-19 UPMIN012-19 Macroglossus minimus 5 4 (80.0) 3 (60.0) UPMIN001-19 UPMIN020-19 UPMIN009-19 UPMIN017-19 Ptenochirus jagori 2 2 (100) 2 (100) UPMIN007-19 UPMIN015-19 UPMIN014-19 Eonycteris spelaea 1 1 (100) 1 (100) UPMIN021-19 UPMIN021-19

Total 29 24 (82.7) 18 (62.1)

Table 2. Molecular identity of local fruit bats based on homology and pairwise distance analysis of fecal mt COI.

% identity with BOLD similarity Morphological ID ear voucher specimen Top Hit Identity (%) Distance to nearest neighbor Cynopterus brachyotis 94.5–98.6 C. brachyotis 95.5–99.5 0.02–0.04 Rousettus amplexicaudatus 97.9–100 R. amplexicaudatus 96.3–99.5 0.01 Macroglossus minimus 94.4–95.4 M. minimus 97.8–98.3 0–0.01 Ptenochirus jagori 100 P. jagori 97.1–100 0.01 Eonycteris spelaea 100 E. spelaea 98.2 0.01

548 Philippine Journal of Science Bacus et al.: Fecal DNA Barcoding on Selected Vol. 150 No. 2, April 2021 Philippine Fruit Bats and E. spelaea also had a high average identity of 97% the Philippines vs. the rest of Asia. The diversity of and 96%, respectively, with conspecific bats outside the E. spelaea was consistently very low for the entire country. However, C. brachyotis and R. amplexicaudatus population (0.4%), for the Philippine and non-Philippine from the Philippines only had 84–86% average identities subpopulations or intra-population (0.3%), and between with their non-Philippine counterparts. the subpopulations or inter-population (0%) (Figure 1B). M. minimus exhibited intermediary diversity of 3% for the entire population, 1.4% for the Philippine and Genetic Relationship of Fruit Bats from the non-Philippine subpopulations, and 1.6% between the Philippines and Asia subpopulations (Figure 1B). In contrast, C. brachyotis To further compare the Philippine fruit bats with those from and R. amplexicaudatus exhibited relatively high outside the country, the sample and reference sequences intraspecific diversity for the entire population (9 and were collectively grouped into two subpopulations – 9.8%, respectively), as well as between the Philippine and

Figure 1. Genetic distance of fruit bats from the Philippines based on mt COI (~ 200 bp): A) average sequence identity (%) of voucher specimens of the indicated bats with Philippine and non-Philippine reference sequences from BOLD; B) mean diversity of each bat species for the entire population available in BOLD, intra-population (Philippine and non-Philippine subgroups), or inter-population (Philippine vs. non-Philippine subgroups). Ptenochirus jagori is endemic to the Philippines.

549 Philippine Journal of Science Bacus et al.: Fecal DNA Barcoding on Selected Vol. 150 No. 2, April 2021 Philippine Fruit Bats non-Philippine subpopulations (6 and 7.2%, respectively), in the database (Figure 3, yellow lines), but the Philippine although the mean subpopulation diversity (2.6–3%) was populations demonstrated divergence from their Asian relatively low (Figure 1B). This is consistent with the counterparts (posterior probability: R. amplexicaudatus = poor sequence identities of the Philippine species with 0.86, M. minimus = 1.0, C. brachyotis = 1.0), except for their conspecifics from outside the country (Figure 1A). E. spelaea wherein the posterior value on the divergence The voucher specimen of the Philippine endemic bat P. between Philippine and Asian populations was only 0.14. jagori corresponded well (99% identity) with P. jagori Different bat species within the same genus were also sequences from other parts of the country (Figure 1A), divergent with posterior probabilities of 0.70–0.97, e.g. with a 2% diversity (Figure 1B). R. amplexicaudatus vs. R. leschenaultii, E. spelaea vs. E. robusta, M. minimus vs. M. sobrinus, C. brachyotis vs. C. PCoA of all bat sequences was also employed as a sphinx, and P. jagori vs. P. minor. separate method for species delineation. Results showed that C. brachyotis, R. amplexicaudatus, and M. minimus from the Philippines formed distinct clusters from their non-Philippine counterparts (Figure 2). C. brachyotis DISCUSSION co-clustered with the Philippine endemic P. jagori. On other hand, all seven individuals of E. spelaea from the Mitochondrial DNA barcodes have been successfully used Philippines were located at one point and clustered with for small mammals even for sequence lengths less than conspecifics outside of the country. 500 bp (Walker et al. 2016; Wilson et al. 2014), which facilitates barcoding of samples obtained from minimally- Phylogenetic analysis was conducted to infer the genetic invasive methods that are sensitive to DNA degradation relationships of the bat samples obtained in this study such as fecal or environmental samples. However, the and other populations available online. All five bat utility of the Species from Feces barcode has not yet species collected in this study formed a monophyletic been explored for Philippine bats, including endemic bat group with their corresponding genus with strong species. This pilot study evaluated the utility of the Species Bayesian posterior probabilities (0.7–1.0) (Figure 3). from Feces barcoding method to selected Philippine fruit Two major monophyletic clades were depicted in the bats with an 83% success rate for PCR amplification and phylogenetic tree – the first of which consisted of 62% for individual barcoding. Although extracted DNA Rousettus spp., Eonycteris spp., and Macroglossus spp. was not detectable in electrophoresis, this is expected for (posterior probability = 0.82) – while the second included difficult samples such as feces. Nevertheless, acquisition the Cynopterus spp. and Ptenochirus spp. (posterior of genetic material from fecal matter can be improved in probability = 0.97), which coincides with the co-clustering future studies through alternative preservation methods of both species in the PCoA (Figure 2). All bats obtained such as nucleic acid storage solutions, FTA cards, or in this study clustered with their Philippine counterparts cryogenic storage that prevent DNA degradation of field-

Figure 2. Principal coordinate analysis of all reference and sampled bats based on mtCOI (~ 200 bp). Cynopterus brachyotis (+), Cynopterus sphinx (-), Rousettus amplexicaudatus (), Rousettus leschenaultii (), Macroglossus minimus (X), Macroglossus sobrinus (), Eonycteris spelaea (), Eonycteris robusta (), Ptenochirus jagori (), and Ptenochirus minor (0); red – Philippines, black – outside Philippines.

550 Philippine Journal of Science Bacus et al.: Fecal DNA Barcoding on Selected Vol. 150 No. 2, April 2021 Philippine Fruit Bats

Figure 3. Bayesian phylogenetic tree constructed using an alignment of partial mitochondrial cytochrome c oxidase 1 (mt CO1) gene of approximately 200 bp for the genus Cynopterus, Rousettus, Macroglossus, Eonycteris, and Ptenochirus. The tree is generated based on the best model available in BEAST (HKY+G), as calculated using jModelTest v.2.1.10 using the BIC. Eidolon helvum from the Middle East and Africa were used as an outgroup. Posterior values are found in the nodes of the tree and the corresponding geographical region of the sample is indicated by the branch color (red – Middle East/Africa, blue – Asia, yellow – Philippines). Sequences from this study are highlighted in red color. acquired samples (Walker et al. 2016; Wilson et al. 2014). and minimize inhibitors to achieve better sequence reads. The PCR protocol for the Species from Feces Method Despite these challenges on working with difficult tissues, has been designed for low-quality and -quantity DNA the ability of the method to obtain genetic information obtained from difficult samples such as feces and body from bat fecal matter with accurate confirmation of the swabs (Walker et al. 2016). In addition, we performed field identification highlights its potential as a tool for chain PCR in order to increase the yield of amplicons ecological surveys using population samples, e.g. fecal for sequencing, which allowed us to amplify 83% of the droppings in roosting sites, and other applications that samples. However, low amplicon yield and/or inhibitors are necessary for proper inventory and documentation of in the feces that remained despite sample processing could local bat community assemblages (Walker et al. 2016). have been responsible for the poor chromatograms in some of the samples. This can be improved by optimizing the The ~ 202-bp mt COI sequence appears to be sufficient post-PCR clean-up process to increase amplicon yield for species discrimination as demonstrated by three

551 Philippine Journal of Science Bacus et al.: Fecal DNA Barcoding on Selected Vol. 150 No. 2, April 2021 Philippine Fruit Bats confirmatory tests: 1) 95–100% identity with database ND2-cytB genetic analysis (Heaney et al. 2005; Peterson sequences, 2) nearest neighbor distance of 0–4% with and Heaney 1993; Roberts 2006). A barcoding initiative Philippine bat sequences from various parts of the country, in Asia estimated that around two thirds of bat taxa will and 3) phylogenetic clustering of query sequences within have a minimum genetic diversity of around 2% (Francis the target species. The Species from Feces method has et al. 2010). Another theory proposed that widespread bat previously achieved mt COI barcode classification species such as R. amplexicaudatus, C. brachyotis, and M. for the genus (~ 96% of the barcode samples) or the minimus – which move across open habitats in disturbed species level (~ 91% of the barcode samples) (Walker areas – show more intra-population genetic variation et al. 2016). Although BLAST, pairwise distance, and than those with limited movements outside their habitat tree-based methods are known to generate high rates of and restricted distribution such as P. jagori (Francis et al. correct identification in DNA barcoding, in the absence 2010; Heaney et al. 2005; Peterson and Heaney 1993). of conspecific reference sequences, the strict tree-based Our results also support the idea that due to genetic drift, phylogenetic approach (i.e. the identity is determined smaller populations such as the endemic P. jagori tend to with certainty only when the query sequence is within lose genetic variation (Heaney et al. 2005) as compared a monospecific clade) has been found to have lower to their widespread sister taxon C. brachyotis. Meanwhile, likelihood of false-positive identifications (Ross et al. E. spelaea is a possible recent colonizer from mainland 2008). The trees generated in this study were similar to Asia to the Philippines (Maharadatunkamsi et al. 2003; that for the standard ~ 500-bp COI and cytB (Bastian et Hisheh et al. 1998), which could explain their minimal al. 2001; Luczon et al. 2019). genetic diversity relative to other bat species. The genetics and evolution of this species in the Philippines is still The five bat species – C. brachyotis, R. amplexicaudatus, unknown (Heaney et al. 2016) and there is only one M. minimus, P. jagori, and E. spelaea – remained previous report on the Philippine E. spelaea that utilized genetically distinct from their closely related species DNA barcoding (Luczon et al. 2019), hence the need to C. sphinx, R. leschenaultii, M. sobrinus, P. minor, and conduct further research on its population genetics, which E. robusta, respectively, based on the 200-bp mt COI could be achieved through collection of more individuals sequences. Previous reports have presented M. minimus for a robust barcode database and the generation of reliable and M. sobrinus as genetically co-clustering, although reference genomes. it was not clear from these phylogenetic trees whether the two species form separate sub-clusters (Francis et al. Based on the interpopulation genetic diversity, Bayesian 2010; Luczon et al. 2019). A detailed visualization of our tree analyses, and PCoA of the mt COI marker, R. phylogenetic tree demonstrated one genetic cluster for amplexicaudatus, C. brachyotis, and M. minimus from the non-Philippine Macroglossus spp. sequences, but it the Philippines demonstrated divergence from their Asian was also evident that M. sobrinus diverged from the M. counterparts. Similar findings have been recently reported minimus lineage to form a sub-clade. This highlights the wherein Philippine R. amplexicaudatus, C. brachyotis, and need to expand more studies on the Macroglossus spp. M. minimus exhibited 6–12% pairwise genetic distance to clearly define their genetic structures. Meanwhile, from their Asian conspecifics based on the 500-bp mt the barcodes were still able to place the samples of P. COI (Luczon et al. 2019). Such high levels of diversity jagori and C. brachyotis on their corresponding field may be already considered as unique species (Francis identity despite the genetic co-clustering of both taxa, et al. 2010). C. brachyotis, R. amplexicaudatus, and M. as confirmed in previous studies (Bastian et al. 2001; minimus have a broad geographical distribution in Asia, Luczon et al. 2019). Since all these bats co-exist in the with C. brachyotis estimated to have colonized the parts Philippines except for C. sphinx, R. leschenaultii, and of the Philippines 1 million years ago (Bastian et al. 2001; M. sobrinus, the ability of this fecal barcoding method Heaney et al. 2016). Several widespread bat species are to accurately identify the five selected fruit bats at the also known to have substantial genetic diversity that can species level illustrates its potential utility for other bat evolve to genetically distinct lineages in isolated regions taxa in the country. (Francis et al. 2010). In fact, the Philippine C. brachyotis has already been suggested to be a distinct population, Findings from this study revealed that genetic diversity with some authors placing it under Cynopterus luzoniensis within a bat species decreased in the following order: (Peters, 1861) (Heaney et al. 2016). E. spelaea, however, R. amplexicaudatus, C. brachyotis, M. minimus, P. showed a strong genetic clustering between the Asian and jagori, and E. spelaea. Similarly, previous studies in the Philippine populations, again confirmed by a previous Philippines have reported that the widespread species R. study (Luczon et al. 2019). These suggest that the amplexicaudatus, C. brachyotis, and M. minimus ranked shorter 200-bp mt COI can capture similar evolutionary high in terms of diversity while the endemic P. jagori relationships for the standard 500-bp mt COI. had low diversity in reference to protein allozyme and

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Walker et al. (2016) has explored the application of Species STATEMENT ON CONFLICT OF from Feces barcoding for taxonomic discrimination. In INTEREST some cases, however, mitochondrial markers may fail to discriminate between bats of separate taxa, as has been The authors declare no conflict of interest. The funders demonstrated for gambianus (Ogilby, 1835) had no role in the design of the study; in the collection, and pusillus (Peters, 1868) in Africa despite analyses, or interpretation of data; in the writing of the their morphological and taxonomic distinction (Nesi et al. manuscript; or in the decision to publish the results. 2011). Hence, fecal barcoding in the Philippines should be expanded to include more taxa, population samples, and sites. Furthermore, the additional ability of this short barcode to replicate findings on diversity and phylogeny NOTES ON APPENDICES from previous studies using other genes (mt COI vs. cytB) The complete appendices section of the study is accessible or gene coverage (200 bp vs 500 bp mt COI-5P) warrants at http://philjournsci.dost.gov.ph further studies to evaluate its use beyond identification to include inferring genetic relationships and population structures, which in turn can help provide insights on population history, biogeography, and taxonomy. REFERENCES BASTIAN ST, TANAKA K, ANUNCIADO RVP, NATURAL NG, SUMALDE AC, NAMIKAWA T. 2001. CONCLUSION Phylogenetic relationships among megachiropteran species from the two major islands of the Philippines This study highlights the utility of fecal DNA barcoding deduced from DNA sequences of cytochrome b gene. as a non-lethal and cost-effective approach for bat Can J Zool 79(9): 1671–1677. surveillance in the Philippines. Future efforts should extend this method to the remaining species of bats in BURGIN CJ, COLELLA JP, KAHN PI, UPHAM NS. the Philippines with large sampling sizes and in various 2018. How many species of mammals are there? J locations to validate its application, including rapid 99(1): 1–14. assessment of bat communities through barcoding of FRANCIS CM. 1989. A comparison of mist nets and two environmental samples. Atypical findings from barcoding designs of harp nets for capturing bats. J Mammal such as mismatches, ambiguous taxonomic placements, 70(4): 865–870. and novel relationships could then serve as a springboard for further genetic analysis using a more comprehensive FRANCIS CM, BORISENKO AV, IVANOVA NV, EGER set of genetic tools. Hence, fecal barcoding may be applied JL, LIM BK. GUILLEN-SERVENT A, KRUSOP SV, as an initial rapid and comprehensive assessment of bat MACKIE I, HEBERT PDN. 2010. The role of DNA assemblages to accelerate ecological surveys and facilitate barcodes in understanding and conservation of mammal immediate response on wildlife conservation. diversity in Southeast Asia. PLoS ONE 5(9): e12575. HALL TA. 1999. BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. Nucleic Acids Symposium Series ACKNOWLEDGMENTS 41: 95–98. This research was funded by the University of the HAMMER O, HARPER DA, RYAN PD. 2001. PAST: Philippines Balik-PhD Program OVPAA BPhD-2016- paleontological statistics software package for 04, the University of the Philippines Mindanao In House education and data analysis. Paleontol Electron 4(1): 9. Research Grant, and the Regional Health Research and Development Council Region XI Philippines. The authors HEANEY LR, WALSH JS, TOWNSEND PETERSON A. would like to thank the Department of Environment and 2005. The roles of geological history and colonization Natural Resources Region XI, the Local Government abilities in genetic differentiation between mammalian Units of Mintal and Malagos, the Malagos Garden Resort, populations in the Philippine archipelago. J Biogeogr the Philippine Eagle Foundation, Alex Tiongco, Roberto 32(2): 229–247. Puentespina Jr., Kemuel Libre Jr., Christian Yancy Yurong, HEANEY LR, BALETE DS, RICKART EA, and Joel C. Navarro for all the assistance and support in NIEDZIELSKI A. 2016. The mammals of Luzon the conduct of this study. island: biogeography and natural history of a Philippine fauna. JHU Press. p. 182–258.

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HEBERT PD, RATNASINGHAM S, DE WAARD JR. PETERSON AT, HEANEY LR. 1993. Genetic 2003. Barcoding animal life: cytochrome c oxidase differentiation in Philippine bats of the genera subunit 1 divergences among closely related species. Cynopterus and Haplonycteris. Biol J Linn Soc 49(3): Proc R Soc Lond B Biol Sci 2003 270(suppl_1): 203–218. S96–S99. PFUNDER M, HOLZGANG O, FREY JE. 2004. HERNANDEZ-DAVILA A, VARGAS JA, MARTINEZ- Development of microarray-based diagnostics of voles MENDEZ N, LIM BK, ENGSTROM MD, ORTEGA and shrews for use in biodiversity monitoring studies, J. 2012. DNA barcoding and genetic diversity of and evaluation of mitochondrial cytochrome oxidase I phyllostomoid bats from the Yucatan Peninsula with vs. Cytochrome b as genetic markers. Mol Ecol 13(5): comparisons to Central America. Mol Ecol Resour 1277–1286. 12(4): 590–597. POSADA D. 2008. jModelTest: phylogenetic model HISHEH S, WESTERMAN M, SCHMITT LH. averaging. Mol Biol Evol 25(7): 1253–1256. 1998. Biogeography of the Indonesian archipelago: RAMBAUT A, DRUMMOND AJ, XIE D, BAELE G, mitochondrial DNA variation in the fruit bat, SUCHARD MA. 2018. Posterior summarization in Eonycteris spelaea. Biological Journal of the Linnean Bayesian phylogenetics using Tracer 1.7. Syst Biol Society 65(3): 329–345. 67(5): 901–904. INGLE NR, HEANEY LR. 1992. A key to the bats of ROBERTS TE. 2006. History, ocean channels, and the Philippine islands. Publication (USA) 1440: 1–44. distance determine phylogeographic patterns in three JONES G, JACOBS DS, KUNZ TH, WILLIG MR, widespread Philippine fruit bats (Pteropodidae). Mol RACEY PA. 2009. Carpe noctem: the importance of Ecol 15(8): 2183–2199. bats as bioindicators. Endangered Species Res 8(1–2): ROSS HA, MURUGAN S, SIBON LI WL. 2008. 93–115. Testing the reliability of genetic methods of species KUMAR S, STECHER G, TAMURA K. 2016. MEGA7: identification via simulation. Syst Biol 57(2): 216–230. molecular evolutionary genetics analysis version 7.0 RUSSO D, VOIGT CC. 2016. The use of automated for bigger datasets. Mol Biol Evol 33(7): 1870–1874. identification of bat echolocation calls in acoustic KUNZ TH, DE TORREZ EB, BAUER D, LOBOVA T, monitoring: a cautionary note for a sound analysis. FLEMING TH. 2011. Ecosystem services provided by Ecol Indic 66: 598–602. bats. Europe 31: 32. SUCHARD MA, LEMEY P, BAELE G, AYRES DL, LIM V, RAMLI R, BHASSU S, WILSON J. 2017. DRUMMOND AJ, RAMBAUT A. 2018. Bayesian A checklist of the bats of Peninsular Malaysia and phylogenetic and phylodynamic data integration using progress towards a DNA barcode reference library. BEAST v.1.10. Vir Evol 4(1): vey016. PLoS ONE 12(7): e0179555. TAMURA K, NEI M, KUMAR S. 2004. Prospects LUCZON AU, AMPO SAMM, ROÑA JGA, DUYA for inferring very large phylogenies by using the MRM, ONG PS, FONTANILLA IKC. 2019. DNA neighbor-joining method. Proc Natl Acad Sci 101(30): barcodes reveal high genetic diversity in Philippine 11030–11035. fruit bats. Philipp J Sci 148(1): 133–140. TANALGO KC, HUGHES AC. 2018. Bats of the MAHARADATUNKAMSI, HISHEH S, KITCHENER Philippine islands – a review of research directions DJ, SCHMITT LH. 2003. Relationships between and relevance to national-level priorities and targets. morphology, genetics, and geography in the cave Mamm Biol 91: 46–56. fruit bat Eonycteris spelaea (Dobson, 1871) from WALKER FM, WILLIAMSON CH, SANCHEZ DE, Indonesia. Biological Journal of the Linnean Society SOBEK CJ, CHAMBERS CL. 2016. Species from 79(4): 511–522. feces: order-wide identification of Chiroptera from NESI N, NAKOUNE E, CRUAUD C, HASSANIN guano and other non-invasive genetic samples. PLoS A. 2011. DNA barcoding of African fruit bats ONE 11(9): e0162342. (Mammalia: Pteropodidae). The mitochondrial genome WILSON JJ, SING KW, HALIM MRA, RAMLI R, does not provide a reliable discrimination between HASHIM R, SOFIAN-AZIRUN M. 2014. Utility of Epomophorus gambianus and Micropteropus pusillus. DNA barcoding for rapid and accurate assessment of C R Biol 334(7): 544–554. bat diversity in Malaysia in the absence of formally described species. Genet Mol Res 13(1): 920–925.

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APPENDIX

Table I. Demographics and morphometrics of fruit bats used in this study. No. according to age Total length Forearm length Tail length Ear length Morphological ID Adult Juvenile No data (mm) (mm) (mm) (mm) C. brachyotis 7 8 0 68–91 60–64 3–10 11–17 R. amplexicaudatus 8 0 0 109–153 82–90 14–28 11–21 M. minimus 4 0 2 65–70 40–42 0 6–14 P. jagori 2 0 1 108–135 83–85 9–14 12–20 E. spelaea 0 1 0 110 47 13 16

Figure I. Representative dorsoventral images of fruit bats in Davao City, Philippines: A) Cynopterus brachyotis, B) Rousettus amplexicaudatus, C) Macroglossus minimus, D) Eonycteris spelaea, and E) Ptenochirus jagori. A–D are voucher specimens while E is a live specimen that was released after photograph was taken. Images are not illustrated to scale.

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