Metagenomic insights into the Impact of Long-Distance Movement on the gut microbiota of wild Asian elephants

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Wild Asian elephants ( Elephas maximus ) are poorly studied, and the 2021 northward movement of a Yunnan wild Asian elephant herd is a natural experiment to explore how long distance movement affects gut microbiome of endangered animals. [Methods] Metagenomics was used to compare fecal samples of long distance movement herd (KM), short distance groups with different geographic relationships (JH,MH) and stable group (CY). The objective was to evaluate the effect of scale of movement on the gut communities in wild Asian elephants. [Results] Long distance movement caused significant changes in gut microbiota.Compared to JH group, KM group showed a significant decrease in gut microbiota (P < 0.05) and changes in gut microbiota (higher community structure) with more heterogeneity between individuals. Key taxa showed higher abundances of environmentally sourced bacteria (Burkholderia), dominant methanogenic archaea (Methanobrevibacter) and a distinct virome (Virome) in the KM group, which was sensitive to habitat changes. For the first time Orthorubulavirus mammalis (zoonotic risk) was detected in the KM group due to cross host virus transmission. [Conclusion] This study show that long-distance movement can change the gut microbiome of wild Asian elephants. The costs of environmental exposure may be incurred and metabolic adaptation may also be signalled. The virome could be used as a biomarker of environmental changes in Asian elephants, warranting further investigation with larger samples. This shows that gut microbiome monitoring may be critical for future health studies and conservation management for wild Asian elephants. Asian elephant Gut microbiome Metagenomics Movement Environmental exposure Conservation biology Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Background Gut microbes are essential for ecological adaptation and health of the endangered species [ 1 – 4 ] . They digest nutrients, regulate immune function and metabolism, and may even affect behavior [ 5 – 8 ] . Gut microbiota are not only bacteria and archaea but also a variety of viruses that may influence host microecological stability, antigen presentation, and immune response [ 9 ] . Gut microbial diversity can affect a person's ability to handle stress, which could be important health indicator [ 10 , 11 ] . Although previous studies showed that changing environment can affect gut microbiota, current research focuses on humans, small mammals, and birds [ 12 – 14 ] . However, little is known about gut microbiota responses in large endangered mammals under extreme movements. Obtaining enough samples is difficult because many wild animals are either unknown and potentially dangerous or threatened/protected [ 15 ] . This gap limits our ability to incorporate microbiomics into the conservation and management of wild animals. Asian elephant ( Elephas maximus ), the largest terrestrial animal and flagship species of Asia, has been threatened with extinction and human interference since the 19th century, and has a very important research model for exploring this problem. Since the 19th century wild Asian elephant populations have decreased steadily because of habitat loss, poaching and other human-induced factors, and are listed in Appendix I of CITES, restricting international trade and strict protection [ 16 ] . In China, the elephant is a national protected wildlife under strict protection. To support their reproduction and survival, the Chinese government has [18, 19]established 11 nature reserves within their known distribution range [ 17 ] . These conservation efforts have triggered a steady increase in the number of Asian elephant populations in China, currently estimated at about 300 individuals [ 18 , 19 ] . However, This growth has also brought new challenges: limited forest carrying capacity drives elephants beyond reserves for food, escalating human-elephant conflicts [ 20 ] . Foraging in human-dominated landscapes also exposes elephants to pesticides and pathogens [ 21 , 22 ] . These pressure may lead to abnormal behavior in elephant herds. In 2021, a herd of wild Asian elephants traveled over 1,000 km north across Yunnan in a short period. This move was likely triggered by a complex combination of ecological and human factors, rather than stable migratory behavior [ 23 ] . Although there are evidence that movement affects the gut microbiome of captive Asian elephants [ 22 ] . Yet, little is known about how such movement affects wild Asian elephants under extreme stress. Unlike seasonal migrations in African elephants [ 24 ] , the studied herd experienced a Non-periodic long-distance movement and it is possible to discuss this question: Does this movement disrupt microbiome stability or induce adaptive reorganization? The northward movement of Asian elephants in Yunnan in 2021 offered a unique opportunity to explore this question. We used high-throughput metagenomics sequencing to compare fecal samples from long-distance movement herds to wild elephant herds with short-distance movement and stable habitats over the same time period. We studied differences in the composition and structure of their bacteria, archaeal and viral communities in terms of impact patterns from long-distance movement. This resulted in new scientific information on health monitoring, conservation and management of wild Asian elephants. Materials and Methods Sample Collection and DNA Extraction A total of 16 fecal samples were collected from wild Asian elephants belonging to four herds(Fig. 1 ). These three categories and four groups create a mobile ecological gradient, spanning from long-distance movement to short-distance movement and settlement. long-distance movement group (KM1-4) : This group refers to the elephant herd that migrated over a long distance from the Xishuangbanna National Nature Reserve (a typical activity area of the Jinghong group) to the outskirts of Kunming in 2021. Fecal samples were collected after their arrival in Jinning District, Kunming's suburbs. Short-distance homogeneous group (JH1-4): These are homogeneous populations of the KM group, and display short- to medium-distance movement behaviors in southwestern Yunnan. Short-distance heterogeneous group (MH1-4): These are heterogeneous populations of the KM group, geographically isolated for approximately 20 years [ 25 ] , and exhibit short-distance movement behaviors. Stable Resident group (CY1-4): This population has been permanently residing within the Nangunhe National Nature Reserve, representing a relatively stable and settled wild elephant population. Although KM and JH are geographically related, differing movement histories warranted separate analysis. In China, wild Asian elephant herds are routinely monitored and identified by professional unmanned aerial vehicle (UAV) monitoring teams [ 26 , 27 ] . Fecal samples were collected only after the herds had left the sampling sites to ensure animal welfare and researcher safety. All samples were collected using a non-invasive approach without any direct contact with the animals. Each sample was transferred into a sterile centrifuge tube, immediately frozen in liquid nitrogen, and subsequently stored at − 80°C until DNA extraction [ 28 ] . DNA Extraction and Sequencing Fecal DNA was extracted using the PowerSoil DNA Isolation Kit (Mo Bio, USA). Concentration was quantified with the Qubit dsDNA HS Assay Kit (Thermo Fisher, USA). Sequencing libraries were prepared with the Illumina Nextera XT Library Preparation Kit (Illumina, San Diego, CA, USA). The quality and concentration of these libraries were evaluated using an Agilent Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA) and the Qubit® system. The library concentration was standardized to 2 nM for 150 bp paired-end sequencing on the Illumina NovaSeq 6000 platform. Base calling and image analysis were conducted with the Illumina standard Pipeline (v1.8.2). Data Processing and Analysis Reads were filtered with fastp v0.23.2 (v0.23.2) [ 29 ] ; host DNA was removed using Bowtie2 v2.4.4 [ 30 ] . Taxonomic classification used Kraken2 and Bracken [ 31 ] . Differential abundance was analyzed with ALDEx2 and DESeq2; α- and β-diversity were computed via vegan and visualized in ggplot2 (R 4.5.1). Results Composition and Abundance of Gut Microbiota After quality control, a total of 437.75 GB of high-quality data was obtained. Rank-Abundance curves (Figure 2, Figure S1) revealed that KM group had steeper curves, indicating lower community uniformity. This suggested that a few species were extremely abundant while most were less so. This study identified a substantial diversity of microbes, including 13,359 bacterial (95 phyla, 629 families, 2,369 genera), 571 archaeal (17 phyla, 59 families, 179 genera), and 2,955 viral (15 phyla, 148 families, 660 genera) (Table S1; Figure S2). The microbial community exhibits typical herbivore hindgut fermenting characteristics. At the phylum level, bacteria such as Pseudomonas, Bacillota, Bacteroidota, and Actinomycetota contributed to fiber degradation and carbohydrate fermentation, while archaea were dominated by Methanobacteriota responsible for methanogenesis. Viruses are mainly represented by Uroviricota, Lenarviricota, and Pisuviricota (Table S2). At the genus level, the bacterial community was predominantly composed of Escherichia, Acinetobacter , Klebsiella , Pseudomonas , and other facultative anaerobic or opportunistic pathogenic genera. Archaea were dominated by Methanobrevibacter and Methanocorpusculum, while the viral community showed high diversity with Xuquatrovirus and Asterius virus. At the species level (Figure 3), the dominant bacteria include E. coli ( Escherichia coli ), K. variicola ( Klebsiella variicola), and L . lactis ( Lactococcus lactis ). These facultative anaerobes primarily facilitate the rapid fermentation of soluble sugars. In contrast, genes associated with the breakdown of complex plant fibers are likely executed by less abundant, yet resilient anaerobes, such as uncultured members of the Lachnospiraceae family and T. bryantii . Regarding viruses, Pseudomonas phage LPPA33, Escherichia phage vB_Ec-M-J, and Klebsiella phage pzk-kv4 were identified. Gut Microbial Diversity Alpha diversity analysis indicated that mobility affects gut microbial richness. At the genus level, KM had significantly lower diversity than JH ( p adj < 0.05). Although the difference between KM and MH was not significant after FDR correction ( p adj = 0.094), the unadjusted p = 0.031 and a substantial effect size (statistic =−2.154) suggest biologically relevant trends. In contrast, KM showed no significant difference from CY (Table S2, Figure 4A, Figure S3A). PERMANOVA analysis revealed that group identity significantly influenced community structure at both genus ( R ² = 0.422, p =0.001) and species levels ( R ² = 0.428, P =0.001) (Appendix S2). PCoA plots showed that KM samples were more dispersive (Figures 4B & S3B). Post-hoc pairwise comparisons showed significant differences in bacterial, archaeal, and viral communities between KM and JH (0.372 ≤ R² ≤ 0.526, 0.023 ≤ P ≤ 0.027). Only the viral community difference between KM and CY reached significance ( R² = 0.335, P = 0.024). This suggests that viruses were more sensitive to habitat changes than bacteria or archaea. Changes in gut microbiota in the movement group A heatmap was generated to compare the relative abundances of microbial taxa at the species level across various movement scales (Figure 6). Among bacteria, members of the Burkholderia complex, such as Burkholderia contaminans and Burkholderia lata , were notably abundant in the KM group. These species, common in soil and water, suggest exposure to human-modified environments. For archaea, the KM group's community composition was particularly distinct, primarily dominated by multiple Methanobrevibacter species (e.g., M. olleyae, M. millera e). As core methanogenic archaea, their high relative abundance in the KM group suggests more active methanogenic metabolic activities in this group's intestines. Two viruses, Alphafusarivirus auriculariae (plant-associated) and Orthorubulavirus mammalis (paramyxovirus with zoonotic potential), were found only in KM, implying novel environmental exposure. Discussion Long-distance Movement Drives Microbiota Change This study compares gut microbiota of long distance and short distance elephant herds by metagenomics and shows that migration affects microbiota by successional reorganization rather than simple disturbance, where viruses respond more strongly to habitat changes than bacteria or archaea, possibly due to their heavy dependency on host organisms. KM had lower α-diversity than JH and evenness supporting disturbance hypothesis. However β-diversity increased suggesting community restructuring and higher inter-individual heterogeneity. These results suggest that disturbance and re-equilibration are transitional processes. Unlike diversity loss in captive species [ 2 , 32 – 36 ] , wild elephants have physiological flexibility enabling temporary microbial reorganization. When KM moved to Kunming their microbiota probably passed a transitional succession several months after relocation. Similar patterns occur in African elephants with seasonal diet [ 24 , 37 ] , but our results represent the first evidence of non-seasonal long distance movement effects in Asian elephants. This approach offers new ecological perspective and important management implications for Asian elephant conservation. Ecological Impact of Key Microbial Taxa The KM group changed habitat type and vegetation structure during migration, which may result in less foraged plants and monotonous food. The high energy consumption and stress responses may contribute to the loss of homeostasis of gut microbiota. The change of species may show exposures to environmental environments during long distance migration. For example, relatively high abundances of Burkholderia contaminans and B. lata (belonged to BCC complex) in the KM group may indicate that the elephant group traveled and got exposed to human activity environments like farmlands and roads. These bacteria are present in various kinds[38] of soils and water bodies and have attracted attention due to their pathogenicity to immunocompromised individuals [ 38 ] . Increased Methanobrevibacter spp. ( M.smithii, M. millerae ) could indicate increased methanogenesis, possibly improving hydrogen utilization efficiency during high energy demand [ 39 ] . This may represent a metabolic strategy to compensate for poor quality high-fiber diets during migration. The interesting pattern is that KM differs significantly in bacterial and archaeological diversity and community structure from sympatric JH and MH groups but not from the geographically isolated CY group. This indicates that diet and habitat use are more important than geographic distance for gut structure [ 40 ] . KM, JH and MH are in similar food sources and selective pressure in human-modified landscapes (farmlands and forest edges [ 41 – 43 ] ), and hence similar population compositions. However, the more stress and frequent shifts in diets due to long-distance movement may have reduced the diversity of bacteria and differentiated the KM group from JH and MH. CY group has long lived nature reserves, feeding mostly on diverse wild plant with minimal disturbance [ 44 ] . Its stable habitat and diet maintains balanced gut microbiota, while KM Herd, currently under community disturbance and reorganization may shift towards a new equilibrium state. Thus, although their niches are distinct, the apparent lack of statistical difference between CY and KM may reflect a temporary convergence in community structure rather than true compositional similarities. Potential Health and Conservation Implications Our results indicate that gut microbiota reflect exposure to environment and host adaptation during long distance movement. O. mammalis , previously found in humans, dogs, pigs and red pandas suggests potential zoonotic interactions [ 45 – 47 ] . Although there is no evidence of infection in elephants, the large host range of this virus indicates that it needs to be monitored in wild populations. A. auriculariae also supports its unique environmental exposure history [ 48 ] . Long distance movement could increase contact with new microbiota and viruses, increasing microbial diversity, and potentially raising health risk. Monitoring these microbial shifts can provide early bioindicators of environmental stress, supporting elephant movement management and health surveillance. The population of Asian elephants in China is steadily increasing, and their distribution range is expanding [ 19 , 49 – 51 ], presenting new challenges for conservation and management. From a conservation perspective, understanding microbiome dynamics aids in evaluating population resilience and optimizing management strategies for human–elephant coexistence. Microbiome as an Indicator for Movement Ecology Our findings reveal the complex nature of the gut ecosystem in wild Asian elephant. Gut microbiota act as a link between host and environment depending on diet, climate and behavior. Movement scale increases, exposure to heterogeneous environments may change networks of microbial networks, changing host physiology and adaptation capacity. Microbial functions relating to energy metabolism, immune regulation and detoxification should be further investigated using metatranscriptomic or metabolomic approaches. Studies with longitudinal sampling and multi-omics data may clarify whether these changes are permanent or stable. Conclusions This study presents new metagenomic evidence showing that long distance movement has important effects on gut microbiota of wild Asian elephants, which offers new perspectives on adaptation of large endangered animals. Rapid environmental changes initiate a transition phase of microbiome reconstruction, characterized by loss of diversity, and new taxa (especially viruses) emerge. Given the frequent dispersal of the Asian elephant population in China, monitoring gut microbiome should be integrated into wildlife management to improve early warning systems for elephant health and support evidence-based conservation planning. Declarations Ethics approval and consent to participate All procedures involving animals were conducted in accordance with relevant national and institutional guidelines. This study was based on field sampling of wild Asian elephants and did not involve any experimental manipulation. Informed consent and permission for sample collection were obtained from the relevant wildlife management authorities responsible for the study areas, and all necessary permits and licences were secured. Consent for publication Not applicable. Availability of data and materials The metagenomic sequencing data generated in this study have been deposited in the China National Center for Bioinformation (CNCB, https://www.cncb.ac.cn/) under the BioProject accession number PRJCA057555 . All data are publicly available. Competing interests The authors declare no competing interests. Funding This study was supported by: National Key R&D Program of China (2023YFF1305000; 2023YFF1305001; 2023YFF130500109); Yunnan Science and Technology Department, High-level Science and Technology Talent and Team Selection Special Program, Technological Innovation Talent Training Project(No. 202405AD350055); Natural Science Foundation of Yunnan Province of China, Yunnan Applied Basic Research Project (No. 202401AT070305); Scientific Support Program of the Southwest Survey and Planning Institute of National Forestry and Grassland Administration (1. Gut Microbial Community Structure of Asian Elephants: A Comparative Study between Captive and Wild States, No. 2024-003; 2. Application of Satellite Tracking Collars in the Monitoring of Wild Asian Elephants in China,No. 2023-005); Support Plan for Revitalizing Yunnan talents" Youth Talent Special Project (No. XDYC-QNRC-2023-0024). Authors' contributions C.F., Y.J.T., and J.S.W. designed the research and wrote the main manuscript. X.P.L. and C.Y. prepared the tables and figures. Z.C.Y., J.S.Z., and D.T.W. participated in sample collection and manuscript review. W.F.D. and H.F. revised the manuscript. All authors reviewed and approved the final version. Acknowledgments This study was generously supported by the National Forestry and Grassland Administration, the Forestry and Grassland Bureaus of Yunnan Province, Jinghong City, and Menghai County, as well as the Xishuangbanna National Nature Reserve and the Yunnan Nangun River National Nature Reserve. We extend our gratitude to Kunming Zhenghao Monitoring Co., Ltd. for their assistance with drone operations during the sampling process. Special thanks are also due to Yong-xiang Li, Cheng-bin Ban, Wen-guang Duang, Zong-xin Pu, and Chao-yong Xiong for their valuable support throughout the sampling activities. References Alberdi A, Aizpurua O, Bohmann K, Zepeda-Mendoza ML, Gilbert MTP. Do Vertebrate Gut Metagenomes Confer Rapid Ecological Adaptation? Trends in Ecology & Evolution. 2016;31:689-699. Huang GP, Shi WY, Wang L, Qu QY, Zuo ZQ, Wang JF, et al. PandaGUT provides new insights into bacterial diversity, function, and resistome landscapes with implications for conservation. Microbiome. 2023;11. Muegge BD, Kuczynski J, Knights D, Clemente JC, González A, Fontana L, et al. Diet Drives Convergence in Gut Microbiome Functions Across Mammalian Phylogeny and Within Humans. Science. 2011;332:970-974. Wei F, Wu Q, Hu Y, Huang G, Nie Y, Yan L. Conservation metagenomics: a new branch of conservation biology. Science China Life Sciences. 2019;62:168-178. Miller CA, Holm HC, Horstmann L, George JC, Fredricks HF, Van Mooy BAS, et al. Coordinated transformation of the gut microbiome and lipidome of bowhead whales provides novel insights into digestion. The ISME Journal. 2020;14:688-701. Koropatkin NM, Cameron EA, Martens EC. How glycan metabolism shapes the human gut microbiota. Nature Reviews Microbiology. 10:323-335. Sylvia KE, Demas GE. A gut feeling: Microbiome-brain-immune interactions modulate social and affective behaviors. Hormones and Behavior. 99:41-49. Lu J, Lu L, Yu Y, Cluette-Brown J, Martin CR, Claud EC. Effects of Intestinal Microbiota on Brain Development in Humanized Gnotobiotic Mice. Scientific Reports. 2018;8. Greene LK, Williams CV, Junge RE, Mahefarisoa KL, Rajaonarivelo T, Rakotondrainibe H, et al. A role for gut microbiota in host niche differentiation. The ISME Journal. 2020;14:1675-1687. Hantsoo L, Zemel BS. Stress gets into the belly: Early life stress and the gut microbiome. Behavioural Brain Research. 414:113474. Hussain Z, Park H. Inflammation and Impaired Gut Physiology in Post-operative Ileus: Mechanisms and the Treatment Options. Journal of Neurogastroenterology and Motility. 2022;28:517-530. Webb SE, Orkin JD, Williamson RE, Melin AD. Activity budget and gut microbiota stability and flexibility across reproductive states in wild capuchin monkeys in a seasonal tropical dry forest. Animal Microbiome. 2023;5. Copeland JK, Chao G, Vanderhout S, Acton E, Wang PW, Benchimol EI, et al. The Impact of Migration on the Gut Metagenome of South Asian Canadians. Gut Microbes. 13:1-29. Obrochta S, Savo Sardaro ML, Amato KR, Murray MH. Relationships Between Migration and Microbiome Composition and Diversity in Urban Canada Geese. Frontiers in Ecology and Evolution. 2022;10. Combrink L, Humphreys IR, Washburn Q, Arnold HK, Stagaman K, Kasschau KD, et al. Best practice for wildlife gut microbiome research: A comprehensive review of methodology for 16S rRNA gene investigations. Frontiers in Microbiology. 2023;14. Sakamoto M. Recent Topics on CITES Related to Asian Elephants in Particular. Gajah. 2017;47:42-44. Wang ZH, Chen F, Yang ZC, Wang. MJ. Research status and prospect of Asian elephant. Forestry Construction. 2021;:6-11. Zhao Y, Jin K. Distribution ,Population ,Habitat Status and Population Management of Asian Elephant. World Forestry Ｒesearch. 2018;31:25-30. Tang YJ, Yang C, Yang ZC, Chen F. Population dynamics of wild Asian elephants over the past fifty years. Acta Theriologica Sinica. 2023;43:593-607. Liu JQ, Wang M, Zhu GF, Li Z, Ma J, Su R, et al. Cognition and Attitude of Villagers on Controlling Protection of Wild Asian Elephants in Xishuangbanna. Chinese Journal of Wildlife. 2022;43:453-462. Cao KX, Wang YP, Bai XW, Wang JS, Zhang LT, Tang YJ, et al. Comparison of Fecal Antimicrobial Resistance Genes in Captive and Wild Asian Elephants. Antibiotics. 2023;12:859. Moustafa MAM, Chel HM, Thu MJ, Bawm S, Htun LL, Win MM, et al. Anthropogenic interferences lead to gut microbiome dysbiosis in Asian elephants and may alter adaptation processes to surrounding environments. Scientific Reports. 2021;11:741. Campos‐Arceiz A, de la Torre JA, Wei K, Wu XO, Zhang Y, Zhu Y, et al. China’s wandering elephants: Integrating exceptional movements into conservation planning. Integrative Conservation. 2022;1:40-51. Budd K, Gunn JC, Finch T, Klymus K, Sitati N, Eggert LS. Effects of diet, habitat, and phylogeny on the fecal microbiome of wild African savanna ( Loxodonta africana ) and forest elephants ( L. cyclotis ). Ecology and Evolution. 2020;10:5637-5650. Wang ZH, Li ZL, Tang YJ, Yao CX, Liu Y, Jiang GL, et al. China’s dams isolate Asian elephants. Science. 2020;367:373-374. Yang N, Dai XH, Wang B, Wen MC, Gan ZL, Li ZL, et al. Mapping potential human-elephant conflict hotspots with UAV monitoring data. Global Ecology and Conservation. 2023;43:e02451. Bao MW, Han Y, Xiong CY, Chen JM, Wang B, Li MF, et al. Individual Identification and Population Quantitative Characteristics of Asian Elephant in the Wild Elephant Valley, Xishuangbanna. Chinese Journal of Wildlife. 2024;45:472-479. Bo ZC. Exploring the Asian Elephant Fecal Microbiomes from Different Living Environments and the Identification of Novel Enzyme Genes for Degrading Lignocellulose. Yunnan Normal University; 2021. Chen S, Zhou Y, Chen Y, Gu J. fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics. 2018;34:i884-i890. Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nature Methods. 2012;9:357-359. Lu J, Breitwieser FP, Thielen P, Salzberg SL. Bracken: estimating species abundance in metagenomics data. PeerJ Computer Science. 2017;3:e104. Gao H, Chi X, Qin W, Wang L, Song P, Cai Z, et al. Comparison of the gut microbiota composition between the wild and captive Tibetan wild ass (Equus kiang). Journal of Applied Microbiology. 2019;126:1869-1878. Gibson KM, Nguyen BN, Neumann LM, Miller M, Buss P, Daniels S, et al. Gut microbiome differences between wild and captive black rhinoceros – implications for rhino health. Scientific Reports. 2019;9. Ning Y, Qi JZ, Dobbins MT, Liang X, Wang J, Chen SY, et al. Comparative Analysis of Microbial Community Structure and Function in the Gut of Wild and Captive Amur Tiger. Frontiers in Microbiology. 2020;11:1665. Klinhom S, Kunasol C, Sriwichaiin S, Kerdphoo S, Chattipakorn N, Chattipakorn SC, et al. Characteristics of gut microbiota profiles in Asian elephants (Elephas maximus) with gastrointestinal disorders. Scientific Reports. 2025;15:1327. Klinsawat W, Uthaipaisanwong P, Jenjaroenpun P, Sripiboon S, Wongsurawat T, Kusonmano K. Microbiome variations among age classes and diets of captive Asian elephants (Elephas maximus) in Thailand using full-length 16S rRNA nanopore sequencing. Scientific Reports. 2023;13. Kartzinel TR, Hsing JC, Musili PM, Brown BRP, Pringle RM. Covariation of diet and gut microbiome in African megafauna. Proceedings of the National Academy of Sciences. 2019;116:23588-23593. Martina P, Bettiol M, Vescina C, Montanaro P, Mannino MC, Prieto CI, et al. Genetic Diversity of Burkholderia contaminans Isolates from Cystic Fibrosis Patients in Argentina. Journal of Clinical Microbiology. 2013;51:339-344. Muegge BD, Kuczynski J, Knights D, Clemente JC, González A, Fontana L, et al. Diet Drives Convergence in Gut Microbiome Functions Across Mammalian Phylogeny and Within Humans. Science. 2011;332:970-974. Guo Q, Zhang W, Xu C, Li X, Wang B, Xiong C, et al. Comparative Analysis of Gut Microbiome Community Structures in Different Populations of Asian Elephants in China and Their Correlation with Diet. Genes. 2025;16:483. Yu Q, Hu Z, Huang C, Xu T, Onditi KO, Li X, et al. Suitable habitats shifting toward human-dominated landscapes of Asian elephants in China. Biodiversity and Conservation. 33:685-704. Xie F, Zhang X, Zhang J, Chen F, Fan H. Interannual dynamics of China’s wild elephant habitat revealed by Landsat-based time series land cover and meta-analysis derived habitat preferences. Landscape Ecology. 2025;40. Huang C, Li X, Khanal L, Jiang X. Habitat suitability and connectivity inform a co-management policy of protected area network for Asian elephants in China. PeerJ. 2019;7:e6791. Wang J, Li X, Duan W, Tian Y, Han R, Meng D, et al. Multi-scale habitat selection and constraints of a small Asian elephant population in Yunnan Nangunhe National Nature Reserve, China. Global Ecology and Conservation. 60:e03616. Chatziandreou N, Stock N, Young D, Andrejeva J, Hagmaier K, McGeoch D, et al. Relationships and host range of human, canine, simian and porcine isolates of simian virus 5 (parainfluenza virus 5). The Journal of general virology. 2004;85:3007-16. Zhai J, Zhai S, Lin T, Liu J, Wang H, Li B, et al. First complete genome sequence of parainfluenza virus 5 isolated from lesser panda. Archives of Virology. 2017;162:1413-1418. Xie J, Tong P, Zhang A, Zhang L, Song X, Kuang L. Identification and Characterization of the First Equine Parainfluenza Virus 5. Virologica Sinica. 2020;35:245-247. Schoch CL, Ciufo S, Domrachev M, Hotton CL, Kannan S, Khovanskaya R, et al. NCBI Taxonomy: a comprehensive update on curation, resources and tools. Database (Oxford). 2020;2020:baaa062. Campos‐Arceiz A, de la Torre JA, Wei K, Wu XO, Zhu Y, Zhao M, et al. The return of the elephants: How two groups of dispersing elephants attracted the attention of billions and what can we learn from their behavior. Conservation Letters. 2021;14. Bai D, Wan XR, Zhang L, Campos-Arceiz A, Wei FW, Zhang ZB. The recent Asian elephant range expansion in Yunnan, China, is associated with climate change and enforced protection efforts in human-dominated landscapes. Frontiers in Ecology and Evolution. 2022;10. Li L-L, Wang Q-Y, Yang H-P, Tao Y-X, Wang L-X, Yang Z-B, et al. Mobile animals and immobile protected areas: improving the coverage of nature reserves for Asian elephant conservation in China. Oryx. 57:532-539. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8699565","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":590100312,"identity":"7289434b-b23e-42da-afc9-ea4ec5f65835","order_by":0,"name":"Fei Chen","email":"","orcid":"","institution":"Yunnan University","correspondingAuthor":false,"prefix":"","firstName":"Fei","middleName":"","lastName":"Chen","suffix":""},{"id":590100313,"identity":"184ce5fe-64ad-47ec-af58-63011e61a371","order_by":1,"name":"Yong-Jing Tang","email":"","orcid":"","institution":"Southwest Survey and Planning Institute of National Forestry and Grassland Administration","correspondingAuthor":false,"prefix":"","firstName":"Yong-Jing","middleName":"","lastName":"Tang","suffix":""},{"id":590100314,"identity":"a3ab4e42-6b54-4b24-8d7e-ab8d0909b702","order_by":2,"name":"Ji-Shan Wang","email":"","orcid":"","institution":"Southwest Survey and Planning Institute of National Forestry and Grassland Administration","correspondingAuthor":false,"prefix":"","firstName":"Ji-Shan","middleName":"","lastName":"Wang","suffix":""},{"id":590100315,"identity":"9a364f60-ccf7-4f3d-83a4-ae28686dad4a","order_by":3,"name":"Xin-Peng Liu","email":"","orcid":"","institution":"Southwest Survey and Planning Institute of National Forestry and Grassland Administration","correspondingAuthor":false,"prefix":"","firstName":"Xin-Peng","middleName":"","lastName":"Liu","suffix":""},{"id":590100316,"identity":"510ad7c1-d3c2-4c44-b336-bbc502f6bfc6","order_by":4,"name":"Zi-Cheng Yang","email":"","orcid":"","institution":"Southwest Survey and Planning Institute of National Forestry and Grassland Administration","correspondingAuthor":false,"prefix":"","firstName":"Zi-Cheng","middleName":"","lastName":"Yang","suffix":""},{"id":590100317,"identity":"6eb11625-177f-4a55-806d-d4476468ea8c","order_by":5,"name":"Cong Yang","email":"","orcid":"","institution":"Southwest Survey and Planning Institute of National Forestry and Grassland Administration","correspondingAuthor":false,"prefix":"","firstName":"Cong","middleName":"","lastName":"Yang","suffix":""},{"id":590100318,"identity":"731823dc-c5bd-431f-aec2-9a5827ed9cbe","order_by":6,"name":"Jian-Song Zhang","email":"","orcid":"","institution":"Southwest Survey and Planning Institute of National Forestry and Grassland Administration","correspondingAuthor":false,"prefix":"","firstName":"Jian-Song","middleName":"","lastName":"Zhang","suffix":""},{"id":590100319,"identity":"41e21a58-dcc0-4d82-bc1d-7ea3bd8cea21","order_by":7,"name":"Dan-Tong Wang","email":"","orcid":"","institution":"Southwest Survey and Planning Institute of National Forestry and Grassland Administration","correspondingAuthor":false,"prefix":"","firstName":"Dan-Tong","middleName":"","lastName":"Wang","suffix":""},{"id":590100320,"identity":"77365e8b-d002-45ac-b43f-ba0ea3dceab5","order_by":8,"name":"Wei-Feng Ding","email":"","orcid":"","institution":"Institute of Highland Forest Science, Chinese Academy of Forestry","correspondingAuthor":false,"prefix":"","firstName":"Wei-Feng","middleName":"","lastName":"Ding","suffix":""},{"id":590100321,"identity":"ddbd667b-b1d3-4ad4-a941-a08ece1e0cef","order_by":9,"name":"Hui Fan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAvklEQVRIiWNgGAWjYBAC9gYGNgYGAxsIj4cYLTwHwFrSSNbCcJgULexnjz3mKTifuF0igfHB2zYGeXOCWnjy0o15DG4n7pyRwGw4t43BcGcDAS32DDlm0iAtG24ksEnztjEkGBwgZAv/G5CWcyAt7L+J0yIBtuUA2BZmIrW8MZOcY5BsvOHMw2bJOeckDDcQdliOmcSbP3ayG44nH/zwpsxGnqAtMODYwMDYAKQliFTPAAq5UTAKRsEoGAW4AADejDr7r1RbpwAAAABJRU5ErkJggg==","orcid":"","institution":"Yunnan University","correspondingAuthor":true,"prefix":"","firstName":"Hui","middleName":"","lastName":"Fan","suffix":""}],"badges":[],"createdAt":"2026-01-26 11:08:52","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8699565/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8699565/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102623517,"identity":"067f54ed-b8cd-48f2-9865-3fca66365a64","added_by":"auto","created_at":"2026-02-13 17:10:23","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":674771,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCollection locations of fecal samples. Different dashed circles represent the distribution ranges of four groups respectively. The movement (orange) and return (green) routes of the KM population reflect their long - distance experiences.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8699565/v1/85d421c4935ce83bb0bd036f.png"},{"id":102623530,"identity":"444f66c9-73c6-4c1e-a666-4981fb6b859b","added_by":"auto","created_at":"2026-02-13 17:10:32","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":46141,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDistribution curve of species abundance grade\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8699565/v1/a8918a16b9d1bbe4948e8a7a.png"},{"id":102623521,"identity":"29c8c169-d767-4bda-90cf-0f1d619ccb2a","added_by":"auto","created_at":"2026-02-13 17:10:24","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":330488,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRelative abundance of major bacteria, archaea and viruses\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8699565/v1/6349c97057f86e396ddd7449.png"},{"id":102623519,"identity":"fc85fa99-20e4-476a-a9e1-f34f6a3e7ecd","added_by":"auto","created_at":"2026-02-13 17:10:23","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":72191,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAnalysis of Gut Microbial Diversity. (A) Box plot illustrating α diversity using the Shannon index. (B) Principal Coordinate Analysis (PCoA) based on Bray-Curtis distance.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8699565/v1/823b20339bf84183daf607c2.png"},{"id":102623525,"identity":"122a7431-b348-4732-aa97-0bcbb6beefd9","added_by":"auto","created_at":"2026-02-13 17:10:27","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":39741,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePERMANOVA (Adonis) Analysis Based on Bray-Curtis Distance. F-value shown in green. R\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e2 \u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003eis shown in blue. *: 0.01 \u0026lt; P ≤ 0.05; **: 0.001 \u0026lt; P ≤ 0.01; ***: P ≤ 0.001 †: P \u0026gt; 0.05 (NS).\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8699565/v1/19df4ed3dc4ed3ca76f0805f.png"},{"id":102623518,"identity":"4c6e3964-b423-4a12-b5e8-0faf2455e0c9","added_by":"auto","created_at":"2026-02-13 17:10:23","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":292175,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHeatmap of differential microbial species abundance. The plot visualizes the results of a differential abundance analysis between multiple groups, with each point corresponding to a microbial taxon. Gray hollow circles represent taxa that were not statistically significant. Light-green hollow circles indicate taxa that were statistically significant in at least one comparison between groups. Purple solid dots denote taxa that were statistically significant across all three group comparisons.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-8699565/v1/49f1ed89042225adb89e7e90.png"},{"id":102750853,"identity":"ddd84d76-15ac-4b1e-8ef5-7f43ab3a40dd","added_by":"auto","created_at":"2026-02-16 09:22:32","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2363364,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8699565/v1/1d71aa4f-1242-48c0-b7c5-7a6aa3b1d2f0.pdf"},{"id":102747926,"identity":"6668c70f-6db8-46e2-b568-14b03b8095c6","added_by":"auto","created_at":"2026-02-16 09:05:36","extension":"zip","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":7118693,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementalFigureandTable.zip","url":"https://assets-eu.researchsquare.com/files/rs-8699565/v1/7a24f5398763cc6093a292dd.zip"}],"financialInterests":"No competing interests reported.","formattedTitle":"Metagenomic insights into the Impact of Long-Distance Movement on the gut microbiota of wild Asian elephants","fulltext":[{"header":"Background","content":"\u003cp\u003eGut microbes are essential for ecological adaptation and health of the endangered species\u003csup\u003e[\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. They digest nutrients, regulate immune function and metabolism, and may even affect behavior\u003csup\u003e[\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. Gut microbiota are not only bacteria and archaea but also a variety of viruses that may influence host microecological stability, antigen presentation, and immune response\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. Gut microbial diversity can affect a person's ability to handle stress, which could be important health indicator\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAlthough previous studies showed that changing environment can affect gut microbiota, current research focuses on humans, small mammals, and birds\u003csup\u003e[\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. However, little is known about gut microbiota responses in large endangered mammals under extreme movements. Obtaining enough samples is difficult because many wild animals are either unknown and potentially dangerous or threatened/protected\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. This gap limits our ability to incorporate microbiomics into the conservation and management of wild animals.\u003c/p\u003e \u003cp\u003eAsian elephant (\u003cem\u003eElephas maximus\u003c/em\u003e), the largest terrestrial animal and flagship species of Asia, has been threatened with extinction and human interference since the 19th century, and has a very important research model for exploring this problem. Since the 19th century wild Asian elephant populations have decreased steadily because of habitat loss, poaching and other human-induced factors, and are listed in Appendix I of CITES, restricting international trade and strict protection\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e. In China, the elephant is a national protected wildlife under strict protection. To support their reproduction and survival, the Chinese government has [18, 19]established 11 nature reserves within their known distribution range\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. These conservation efforts have triggered a steady increase in the number of Asian elephant populations in China, currently estimated at about 300 individuals\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. However, This growth has also brought new challenges: limited forest carrying capacity drives elephants beyond reserves for food, escalating human-elephant conflicts\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. Foraging in human-dominated landscapes also exposes elephants to pesticides and pathogens\u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. These pressure may lead to abnormal behavior in elephant herds. In 2021, a herd of wild Asian elephants traveled over 1,000 km north across Yunnan in a short period. This move was likely triggered by a complex combination of ecological and human factors, rather than stable migratory behavior\u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e. Although there are evidence that movement affects the gut microbiome of captive Asian elephants\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. Yet, little is known about how such movement affects wild Asian elephants under extreme stress. Unlike seasonal migrations in African elephants\u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e, the studied herd experienced a Non-periodic long-distance movement and it is possible to discuss this question: Does this movement disrupt microbiome stability or induce adaptive reorganization? The northward movement of Asian elephants in Yunnan in 2021 offered a unique opportunity to explore this question.\u003c/p\u003e \u003cp\u003eWe used high-throughput metagenomics sequencing to compare fecal samples from long-distance movement herds to wild elephant herds with short-distance movement and stable habitats over the same time period. We studied differences in the composition and structure of their bacteria, archaeal and viral communities in terms of impact patterns from long-distance movement. This resulted in new scientific information on health monitoring, conservation and management of wild Asian elephants.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSample Collection and DNA Extraction\u003c/h2\u003e \u003cp\u003eA total of 16 fecal samples were collected from wild Asian elephants belonging to four herds(Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). These three categories and four groups create a mobile ecological gradient, spanning from long-distance movement to short-distance movement and settlement.\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003elong-distance movement group (KM1-4) : This group refers to the elephant herd that migrated over a long distance from the Xishuangbanna National Nature Reserve (a typical activity area of the Jinghong group) to the outskirts of Kunming in 2021. Fecal samples were collected after their arrival in Jinning District, Kunming's suburbs.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eShort-distance homogeneous group (JH1-4): These are homogeneous populations of the KM group, and display short- to medium-distance movement behaviors in southwestern Yunnan.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eShort-distance heterogeneous group (MH1-4): These are heterogeneous populations of the KM group, geographically isolated for approximately 20 years\u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e, and exhibit short-distance movement behaviors.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eStable Resident group (CY1-4): This population has been permanently residing within the Nangunhe National Nature Reserve, representing a relatively stable and settled wild elephant population.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eAlthough KM and JH are geographically related, differing movement histories warranted separate analysis.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn China, wild Asian elephant herds are routinely monitored and identified by professional unmanned aerial vehicle (UAV) monitoring teams\u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e. Fecal samples were collected only after the herds had left the sampling sites to ensure animal welfare and researcher safety. All samples were collected using a non-invasive approach without any direct contact with the animals. Each sample was transferred into a sterile centrifuge tube, immediately frozen in liquid nitrogen, and subsequently stored at \u0026minus;\u0026thinsp;80\u0026deg;C until DNA extraction\u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDNA Extraction and Sequencing\u003c/h3\u003e\n\u003cp\u003eFecal DNA was extracted using the PowerSoil DNA Isolation Kit (Mo Bio, USA). Concentration was quantified with the Qubit dsDNA HS Assay Kit (Thermo Fisher, USA). Sequencing libraries were prepared with the Illumina Nextera XT Library Preparation Kit (Illumina, San Diego, CA, USA). The quality and concentration of these libraries were evaluated using an Agilent Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA) and the Qubit\u0026reg; system. The library concentration was standardized to 2 nM for 150 bp paired-end sequencing on the Illumina NovaSeq 6000 platform. Base calling and image analysis were conducted with the Illumina standard Pipeline (v1.8.2).\u003c/p\u003e\n\u003ch3\u003eData Processing and Analysis\u003c/h3\u003e\n\u003cp\u003eReads were filtered with fastp v0.23.2 (v0.23.2)\u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e; host DNA was removed using Bowtie2 v2.4.4\u003csup\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/sup\u003e. Taxonomic classification used Kraken2 and Bracken\u003csup\u003e[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e. Differential abundance was analyzed with ALDEx2 and DESeq2; α- and β-diversity were computed via vegan and visualized in ggplot2 (R 4.5.1).\u003c/p\u003e"},{"header":"Results","content":"\u003ch2\u003eComposition and Abundance of Gut Microbiota\u003c/h2\u003e\n\u003cp\u003eAfter quality control, a total of 437.75 GB of high-quality data was obtained. Rank-Abundance curves (Figure 2, Figure S1) revealed that KM group had steeper curves, indicating lower community uniformity. This suggested that a few species were extremely abundant while most were less so.\u003c/p\u003e\n\u003cp\u003eThis study identified a substantial diversity of microbes, including 13,359 bacterial (95 phyla, 629 families, 2,369 genera), 571 archaeal (17 phyla, 59 families, 179 genera), and 2,955 viral (15 phyla, 148 families, 660 genera) (Table S1; Figure S2). The microbial community exhibits typical herbivore hindgut fermenting characteristics. At the phylum level, bacteria such as Pseudomonas, Bacillota, Bacteroidota, and Actinomycetota contributed to fiber degradation and carbohydrate fermentation, while archaea were dominated by Methanobacteriota responsible for methanogenesis. Viruses are mainly represented by Uroviricota, Lenarviricota, and Pisuviricota (Table S2).\u003c/p\u003e\n\u003cp\u003eAt the genus level, the bacterial community was predominantly composed of Escherichia, \u003cem\u003eAcinetobacter\u003c/em\u003e, \u003cem\u003eKlebsiella\u003c/em\u003e, \u003cem\u003ePseudomonas\u003c/em\u003e, and other \u003cem\u003efacultative\u0026nbsp;\u003c/em\u003eanaerobic or opportunistic pathogenic genera. Archaea were dominated by Methanobrevibacter and Methanocorpusculum, while the viral community showed high diversity with Xuquatrovirus and Asterius virus.\u003c/p\u003e\n\u003cp\u003eAt the species level (Figure 3), the dominant bacteria include \u003cem\u003eE. coli\u003c/em\u003e (\u003cem\u003eEscherichia coli\u003c/em\u003e), \u003cem\u003eK. variicola\u003c/em\u003e (\u003cem\u003eKlebsiella variicola),\u003c/em\u003e and \u003cem\u003eL\u003c/em\u003e. \u003cem\u003elactis\u0026nbsp;\u003c/em\u003e(\u003cem\u003eLactococcus lactis\u003c/em\u003e). These facultative anaerobes primarily facilitate the rapid fermentation of soluble sugars. In contrast, genes associated with the breakdown of complex plant fibers are likely executed by less abundant, yet resilient anaerobes, such as uncultured members of the Lachnospiraceae family and \u003cem\u003eT. bryantii\u003c/em\u003e. Regarding viruses, Pseudomonas phage LPPA33, Escherichia phage vB_Ec-M-J, and Klebsiella phage pzk-kv4 were identified.\u003c/p\u003e\n\u003ch2\u003eGut Microbial Diversity\u003c/h2\u003e\n\u003cp\u003eAlpha diversity analysis indicated that mobility affects gut microbial richness. At the genus level, KM had significantly lower diversity than JH (\u003cem\u003ep\u003c/em\u003e \u003cem\u003eadj\u003c/em\u003e \u0026lt; 0.05). Although the difference between KM and MH was not significant after FDR correction (\u003cem\u003ep\u003c/em\u003e \u003cem\u003eadj\u003c/em\u003e = 0.094), the unadjusted \u003cem\u003ep\u003c/em\u003e = 0.031 and a substantial effect size (statistic =\u0026minus;2.154) suggest biologically relevant trends. In contrast, KM showed no significant difference from CY (Table S2, Figure 4A, Figure S3A). \u0026nbsp;PERMANOVA analysis revealed that group identity significantly influenced community structure at both genus (\u003cem\u003eR\u003c/em\u003e\u003cem\u003e\u0026sup2;\u003c/em\u003e = 0.422, \u003cem\u003ep\u0026nbsp;\u003c/em\u003e=0.001) and species levels (\u003cem\u003eR\u003c/em\u003e\u003cem\u003e\u0026sup2;\u003c/em\u003e = 0.428, \u003cem\u003eP\u003c/em\u003e =0.001) (Appendix S2). PCoA plots showed that KM samples were more dispersive (Figures 4B \u0026amp; S3B).\u003c/p\u003e\n\u003cp\u003ePost-hoc pairwise comparisons showed significant differences in bacterial, archaeal, and viral communities between KM and JH (0.372 \u0026le; \u003cem\u003eR\u0026sup2;\u003c/em\u003e \u0026le; 0.526, 0.023 \u0026le; \u003cem\u003eP\u003c/em\u003e \u0026le; 0.027). Only the viral community difference between KM and CY reached significance (\u003cem\u003eR\u0026sup2;\u003c/em\u003e = 0.335, \u003cem\u003eP\u003c/em\u003e = 0.024). This suggests that viruses were more sensitive to habitat changes than bacteria or archaea.\u003c/p\u003e\n\u003ch2\u003eChanges in gut microbiota in the movement group\u003c/h2\u003e\n\u003cp\u003eA heatmap was generated to compare the relative abundances of microbial taxa at the species level across various movement scales (Figure 6). Among bacteria, members of the Burkholderia complex, such as \u003cem\u003eBurkholderia contaminans\u0026nbsp;\u003c/em\u003eand \u003cem\u003eBurkholderia lata\u003c/em\u003e, were notably abundant in the KM group. These species, common in soil and water, suggest exposure to human-modified environments. For archaea, the KM group\u0026apos;s community composition was particularly distinct, primarily dominated by multiple \u003cem\u003eMethanobrevibacter\u0026nbsp;\u003c/em\u003especies (e.g., \u003cem\u003eM. olleyae, M. millera\u003c/em\u003ee). As core \u003cem\u003emethanogenic\u0026nbsp;\u003c/em\u003earchaea, their high relative abundance in the KM group suggests more active \u003cem\u003emethanogenic\u0026nbsp;\u003c/em\u003emetabolic activities in this group\u0026apos;s intestines. Two viruses, \u003cem\u003eAlphafusarivirus auriculariae\u003c/em\u003e (plant-associated) and \u003cem\u003eOrthorubulavirus mammalis\u003c/em\u003e (paramyxovirus with zoonotic potential), were found only in KM, implying novel environmental exposure.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eLong-distance Movement Drives Microbiota Change\u003c/h2\u003e \u003cp\u003eThis study compares gut microbiota of long distance and short distance elephant herds by metagenomics and shows that migration affects microbiota by successional reorganization rather than simple disturbance, where viruses respond more strongly to habitat changes than bacteria or archaea, possibly due to their heavy dependency on host organisms. KM had lower α-diversity than JH and evenness supporting disturbance hypothesis. However β-diversity increased suggesting community restructuring and higher inter-individual heterogeneity. These results suggest that disturbance and re-equilibration are transitional processes. Unlike diversity loss in captive species\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan additionalcitationids=\"CR33 CR34 CR35\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/sup\u003e, wild elephants have physiological flexibility enabling temporary microbial reorganization. When KM moved to Kunming their microbiota probably passed a transitional succession several months after relocation. Similar patterns occur in African elephants with seasonal diet\u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/sup\u003e, but our results represent the first evidence of non-seasonal long distance movement effects in Asian elephants. This approach offers new ecological perspective and important management implications for Asian elephant conservation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eEcological Impact of Key Microbial Taxa\u003c/h2\u003e \u003cp\u003eThe KM group changed habitat type and vegetation structure during migration, which may result in less foraged plants and monotonous food. The high energy consumption and stress responses may contribute to the loss of homeostasis of gut microbiota. The change of species may show exposures to environmental environments during long distance migration. For example, relatively high abundances of \u003cem\u003eBurkholderia contaminans\u003c/em\u003e and \u003cem\u003eB. lata\u003c/em\u003e (belonged to BCC complex) in the KM group may indicate that the elephant group traveled and got exposed to human activity environments like farmlands and roads. These bacteria are present in various kinds[38] of soils and water bodies and have attracted attention due to their pathogenicity to immunocompromised individuals\u003csup\u003e[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003c/sup\u003e. Increased \u003cem\u003eMethanobrevibacter\u003c/em\u003e spp. (\u003cem\u003eM.smithii, M. millerae\u003c/em\u003e) could indicate increased methanogenesis, possibly improving hydrogen utilization efficiency during high energy demand\u003csup\u003e[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]\u003c/sup\u003e. This may represent a metabolic strategy to compensate for poor quality high-fiber diets during migration.\u003c/p\u003e \u003cp\u003eThe interesting pattern is that KM differs significantly in bacterial and archaeological diversity and community structure from sympatric JH and MH groups but not from the geographically isolated CY group. This indicates that diet and habitat use are more important than geographic distance for gut structure\u003csup\u003e[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]\u003c/sup\u003e. KM, JH and MH are in similar food sources and selective pressure in human-modified landscapes (farmlands and forest edges\u003csup\u003e[\u003cspan additionalcitationids=\"CR42\" citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]\u003c/sup\u003e), and hence similar population compositions. However, the more stress and frequent shifts in diets due to long-distance movement may have reduced the diversity of bacteria and differentiated the KM group from JH and MH. CY group has long lived nature reserves, feeding mostly on diverse wild plant with minimal disturbance\u003csup\u003e[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]\u003c/sup\u003e. Its stable habitat and diet maintains balanced gut microbiota, while KM Herd, currently under community disturbance and reorganization may shift towards a new equilibrium state. Thus, although their niches are distinct, the apparent lack of statistical difference between CY and KM may reflect a temporary convergence in community structure rather than true compositional similarities.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003ePotential Health and Conservation Implications\u003c/h2\u003e \u003cp\u003eOur results indicate that gut microbiota reflect exposure to environment and host adaptation during long distance movement. \u003cem\u003eO. mammalis\u003c/em\u003e, previously found in humans, dogs, pigs and red pandas suggests potential zoonotic interactions\u003csup\u003e[\u003cspan additionalcitationids=\"CR46\" citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]\u003c/sup\u003e. Although there is no evidence of infection in elephants, the large host range of this virus indicates that it needs to be monitored in wild populations. \u003cem\u003eA. auriculariae\u003c/em\u003e also supports its unique environmental exposure history\u003csup\u003e[\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]\u003c/sup\u003e. Long distance movement could increase contact with new microbiota and viruses, increasing microbial diversity, and potentially raising health risk. Monitoring these microbial shifts can provide early bioindicators of environmental stress, supporting elephant movement management and health surveillance.\u003c/p\u003e \u003cp\u003eThe population of Asian elephants in China is steadily increasing, and their distribution range is expanding\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan additionalcitationids=\"CR50\" citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e],\u003c/sup\u003e presenting new challenges for conservation and management. From a conservation perspective, understanding microbiome dynamics aids in evaluating population resilience and optimizing management strategies for human\u0026ndash;elephant coexistence.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eMicrobiome as an Indicator for Movement Ecology\u003c/h2\u003e \u003cp\u003eOur findings reveal the complex nature of the gut ecosystem in wild Asian elephant. Gut microbiota act as a link between host and environment depending on diet, climate and behavior. Movement scale increases, exposure to heterogeneous environments may change networks of microbial networks, changing host physiology and adaptation capacity. Microbial functions relating to energy metabolism, immune regulation and detoxification should be further investigated using metatranscriptomic or metabolomic approaches. Studies with longitudinal sampling and multi-omics data may clarify whether these changes are permanent or stable.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study presents new metagenomic evidence showing that long distance movement has important effects on gut microbiota of wild Asian elephants, which offers new perspectives on adaptation of large endangered animals. Rapid environmental changes initiate a transition phase of microbiome reconstruction, characterized by loss of diversity, and new taxa (especially viruses) emerge. Given the frequent dispersal of the Asian elephant population in China, monitoring gut microbiome should be integrated into wildlife management to improve early warning systems for elephant health and support evidence-based conservation planning.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch3\u003eEthics approval and consent to participate\u003c/h3\u003e\n\u003cp\u003eAll procedures involving animals were conducted in accordance with relevant national and institutional guidelines. This study was based on field sampling of wild Asian elephants and did not involve any experimental manipulation. Informed consent and permission for sample collection were obtained from the relevant wildlife management authorities responsible for the study areas, and all necessary permits and licences were secured.\u003c/p\u003e\n\u003ch3\u003eConsent for publication\u003c/h3\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch3\u003eAvailability of data and materials\u003c/h3\u003e\n\u003cp\u003eThe metagenomic sequencing data generated in this study have been deposited in the China National Center for Bioinformation (CNCB, https://www.cncb.ac.cn/) under the BioProject accession number \u003cstrong\u003ePRJCA057555\u003c/strong\u003e. All data are publicly available.\u003c/p\u003e\n\u003ch3\u003eCompeting interests\u003c/h3\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003ch3\u003eFunding\u003c/h3\u003e\n\u003cp\u003eThis study was supported by: National Key R\u0026amp;D Program of China (2023YFF1305000; 2023YFF1305001; 2023YFF130500109); Yunnan Science and Technology Department, High-level Science and Technology Talent and Team Selection Special Program, Technological Innovation Talent Training Project(No. 202405AD350055); Natural Science Foundation of Yunnan Province of China, Yunnan Applied Basic Research Project (No. 202401AT070305); Scientific Support Program of the Southwest Survey and Planning Institute of National Forestry and Grassland Administration (1. Gut Microbial Community Structure of Asian Elephants: A Comparative Study between Captive and Wild States, No. 2024-003; 2. Application of Satellite Tracking Collars in the Monitoring of Wild Asian Elephants in China,No. 2023-005); Support Plan for Revitalizing Yunnan talents\u0026quot; Youth Talent Special Project (No. XDYC-QNRC-2023-0024).\u003c/p\u003e\n\u003ch3\u003eAuthors\u0026apos; contributions\u003c/h3\u003e\n\u003cp\u003eC.F., Y.J.T., and J.S.W. designed the research and wrote the main manuscript. X.P.L. and C.Y. prepared the tables and figures. Z.C.Y., J.S.Z., and D.T.W. participated in sample collection and manuscript review. W.F.D. and H.F. revised the manuscript. All authors reviewed and approved the final version.\u003c/p\u003e\n\u003ch3\u003eAcknowledgments\u003c/h3\u003e\n\u003cp\u003eThis study was generously supported by the National Forestry and Grassland Administration, the Forestry and Grassland Bureaus of Yunnan Province, Jinghong City, and Menghai County, as well as the Xishuangbanna National Nature Reserve and the Yunnan Nangun River National Nature Reserve. We extend our gratitude to Kunming Zhenghao Monitoring Co., Ltd. for their assistance with drone operations during the sampling process. Special thanks are also due to Yong-xiang Li, Cheng-bin Ban, Wen-guang Duang, Zong-xin Pu, and Chao-yong Xiong for their valuable support throughout the sampling activities.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAlberdi A, Aizpurua O, Bohmann K, Zepeda-Mendoza ML, Gilbert MTP. Do Vertebrate Gut Metagenomes Confer Rapid Ecological Adaptation? Trends in Ecology \u0026amp; Evolution. 2016;31:689-699.\u003c/li\u003e\n\u003cli\u003eHuang GP, Shi WY, Wang L, Qu QY, Zuo ZQ, Wang JF, et al. PandaGUT provides new insights into bacterial diversity, function, and resistome landscapes with implications for conservation. Microbiome. 2023;11.\u003c/li\u003e\n\u003cli\u003eMuegge BD, Kuczynski J, Knights D, Clemente JC, Gonz\u0026aacute;lez A, Fontana L, et al. Diet Drives Convergence in Gut Microbiome Functions Across Mammalian Phylogeny and Within Humans. Science. 2011;332:970-974.\u003c/li\u003e\n\u003cli\u003eWei F, Wu Q, Hu Y, Huang G, Nie Y, Yan L. Conservation metagenomics: a new branch of conservation biology. Science China Life Sciences. 2019;62:168-178.\u003c/li\u003e\n\u003cli\u003eMiller CA, Holm HC, Horstmann L, George JC, Fredricks HF, Van Mooy BAS, et al. Coordinated transformation of the gut microbiome and lipidome of bowhead whales provides novel insights into digestion. The ISME Journal. 2020;14:688-701.\u003c/li\u003e\n\u003cli\u003eKoropatkin NM, Cameron EA, Martens EC. How glycan metabolism shapes the human gut microbiota. Nature Reviews Microbiology. 10:323-335.\u003c/li\u003e\n\u003cli\u003eSylvia KE, Demas GE. A gut feeling: Microbiome-brain-immune interactions modulate social and affective behaviors. Hormones and Behavior. 99:41-49.\u003c/li\u003e\n\u003cli\u003eLu J, Lu L, Yu Y, Cluette-Brown J, Martin CR, Claud EC. Effects of Intestinal Microbiota on Brain Development in Humanized Gnotobiotic Mice. Scientific Reports. 2018;8.\u003c/li\u003e\n\u003cli\u003eGreene LK, Williams CV, Junge RE, Mahefarisoa KL, Rajaonarivelo T, Rakotondrainibe H, et al. A role for gut microbiota in host niche differentiation. The ISME Journal. 2020;14:1675-1687.\u003c/li\u003e\n\u003cli\u003eHantsoo L, Zemel BS. Stress gets into the belly: Early life stress and the gut microbiome. Behavioural Brain Research. 414:113474.\u003c/li\u003e\n\u003cli\u003eHussain Z, Park H. Inflammation and Impaired Gut Physiology in Post-operative Ileus: Mechanisms and the Treatment Options. Journal of Neurogastroenterology and Motility. 2022;28:517-530.\u003c/li\u003e\n\u003cli\u003eWebb SE, Orkin JD, Williamson RE, Melin AD. Activity budget and gut microbiota stability and flexibility across reproductive states in wild capuchin monkeys in a seasonal tropical dry forest. Animal Microbiome. 2023;5.\u003c/li\u003e\n\u003cli\u003eCopeland JK, Chao G, Vanderhout S, Acton E, Wang PW, Benchimol EI, et al. The Impact of Migration on the Gut Metagenome of South Asian Canadians. Gut Microbes. 13:1-29.\u003c/li\u003e\n\u003cli\u003eObrochta S, Savo Sardaro ML, Amato KR, Murray MH. Relationships Between Migration and Microbiome Composition and Diversity in Urban Canada Geese. Frontiers in Ecology and Evolution. 2022;10.\u003c/li\u003e\n\u003cli\u003eCombrink L, Humphreys IR, Washburn Q, Arnold HK, Stagaman K, Kasschau KD, et al. Best practice for wildlife gut microbiome research: A comprehensive review of methodology for 16S rRNA gene investigations. Frontiers in Microbiology. 2023;14.\u003c/li\u003e\n\u003cli\u003eSakamoto M. Recent Topics on CITES Related to Asian Elephants in Particular. Gajah. 2017;47:42-44.\u003c/li\u003e\n\u003cli\u003eWang ZH, Chen F, Yang ZC, Wang. MJ. Research status and prospect of Asian elephant. Forestry Construction. 2021;:6-11.\u003c/li\u003e\n\u003cli\u003eZhao Y, Jin K. Distribution ,Population ,Habitat Status and Population Management of Asian Elephant. World Forestry Ｒesearch. 2018;31:25-30.\u003c/li\u003e\n\u003cli\u003eTang YJ, Yang C, Yang ZC, Chen F. Population dynamics of wild Asian elephants over the past fifty years. Acta Theriologica Sinica. 2023;43:593-607.\u003c/li\u003e\n\u003cli\u003eLiu JQ, Wang M, Zhu GF, Li Z, Ma J, Su R, et al. Cognition and Attitude of Villagers on Controlling Protection of Wild Asian Elephants in Xishuangbanna. Chinese Journal of Wildlife. 2022;43:453-462.\u003c/li\u003e\n\u003cli\u003eCao KX, Wang YP, Bai XW, Wang JS, Zhang LT, Tang YJ, et al. Comparison of Fecal Antimicrobial Resistance Genes in Captive and Wild Asian Elephants. Antibiotics. 2023;12:859.\u003c/li\u003e\n\u003cli\u003eMoustafa MAM, Chel HM, Thu MJ, Bawm S, Htun LL, Win MM, et al. Anthropogenic interferences lead to gut microbiome dysbiosis in Asian elephants and may alter adaptation processes to surrounding environments. Scientific Reports. 2021;11:741.\u003c/li\u003e\n\u003cli\u003eCampos‐Arceiz A, de la Torre JA, Wei K, Wu XO, Zhang Y, Zhu Y, et al. China\u0026rsquo;s wandering elephants: Integrating exceptional movements into conservation planning. Integrative Conservation. 2022;1:40-51.\u003c/li\u003e\n\u003cli\u003eBudd K, Gunn JC, Finch T, Klymus K, Sitati N, Eggert LS. Effects of diet, habitat, and phylogeny on the fecal microbiome of wild African savanna (\u003cem\u003eLoxodonta africana\u003c/em\u003e) and forest elephants (\u003cem\u003eL. cyclotis\u003c/em\u003e). Ecology and Evolution. 2020;10:5637-5650.\u003c/li\u003e\n\u003cli\u003eWang ZH, Li ZL, Tang YJ, Yao CX, Liu Y, Jiang GL, et al. China\u0026rsquo;s dams isolate Asian elephants. Science. 2020;367:373-374.\u003c/li\u003e\n\u003cli\u003eYang N, Dai XH, Wang B, Wen MC, Gan ZL, Li ZL, et al. Mapping potential human-elephant conflict hotspots with UAV monitoring data. Global Ecology and Conservation. 2023;43:e02451.\u003c/li\u003e\n\u003cli\u003eBao MW, Han Y, Xiong CY, Chen JM, Wang B, Li MF, et al. Individual Identification and Population Quantitative Characteristics of Asian Elephant in the Wild Elephant Valley, Xishuangbanna. Chinese Journal of Wildlife. 2024;45:472-479.\u003c/li\u003e\n\u003cli\u003eBo ZC. Exploring the Asian Elephant Fecal Microbiomes from Different Living Environments and the Identification of Novel Enzyme Genes for Degrading Lignocellulose. Yunnan Normal University; 2021.\u003c/li\u003e\n\u003cli\u003eChen S, Zhou Y, Chen Y, Gu J. fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics. 2018;34:i884-i890.\u003c/li\u003e\n\u003cli\u003eLangmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nature Methods. 2012;9:357-359.\u003c/li\u003e\n\u003cli\u003eLu J, Breitwieser FP, Thielen P, Salzberg SL. Bracken: estimating species abundance in metagenomics data. PeerJ Computer Science. 2017;3:e104.\u003c/li\u003e\n\u003cli\u003eGao H, Chi X, Qin W, Wang L, Song P, Cai Z, et al. Comparison of the gut microbiota composition between the wild and captive Tibetan wild ass (Equus kiang). Journal of Applied Microbiology. 2019;126:1869-1878.\u003c/li\u003e\n\u003cli\u003eGibson KM, Nguyen BN, Neumann LM, Miller M, Buss P, Daniels S, et al. Gut microbiome differences between wild and captive black rhinoceros \u0026ndash; implications for rhino health. Scientific Reports. 2019;9.\u003c/li\u003e\n\u003cli\u003eNing Y, Qi JZ, Dobbins MT, Liang X, Wang J, Chen SY, et al. Comparative Analysis of Microbial Community Structure and Function in the Gut of Wild and Captive Amur Tiger. Frontiers in Microbiology. 2020;11:1665.\u003c/li\u003e\n\u003cli\u003eKlinhom S, Kunasol C, Sriwichaiin S, Kerdphoo S, Chattipakorn N, Chattipakorn SC, et al. Characteristics of gut microbiota profiles in Asian elephants (Elephas maximus) with gastrointestinal disorders. Scientific Reports. 2025;15:1327.\u003c/li\u003e\n\u003cli\u003eKlinsawat W, Uthaipaisanwong P, Jenjaroenpun P, Sripiboon S, Wongsurawat T, Kusonmano K. Microbiome variations among age classes and diets of captive Asian elephants (Elephas maximus) in Thailand using full-length 16S rRNA nanopore sequencing. Scientific Reports. 2023;13.\u003c/li\u003e\n\u003cli\u003eKartzinel TR, Hsing JC, Musili PM, Brown BRP, Pringle RM. Covariation of diet and gut microbiome in African megafauna. Proceedings of the National Academy of Sciences. 2019;116:23588-23593.\u003c/li\u003e\n\u003cli\u003eMartina P, Bettiol M, Vescina C, Montanaro P, Mannino MC, Prieto CI, et al. Genetic Diversity of Burkholderia contaminans Isolates from Cystic Fibrosis Patients in Argentina. Journal of Clinical Microbiology. 2013;51:339-344.\u003c/li\u003e\n\u003cli\u003eMuegge BD, Kuczynski J, Knights D, Clemente JC, Gonz\u0026aacute;lez A, Fontana L, et al. Diet Drives Convergence in Gut Microbiome Functions Across Mammalian Phylogeny and Within Humans. Science. 2011;332:970-974.\u003c/li\u003e\n\u003cli\u003eGuo Q, Zhang W, Xu C, Li X, Wang B, Xiong C, et al. Comparative Analysis of Gut Microbiome Community Structures in Different Populations of Asian Elephants in China and Their Correlation with Diet. Genes. 2025;16:483.\u003c/li\u003e\n\u003cli\u003eYu Q, Hu Z, Huang C, Xu T, Onditi KO, Li X, et al. Suitable habitats shifting toward human-dominated landscapes of Asian elephants in China. Biodiversity and Conservation. 33:685-704.\u003c/li\u003e\n\u003cli\u003eXie F, Zhang X, Zhang J, Chen F, Fan H. Interannual dynamics of China\u0026rsquo;s wild elephant habitat revealed by Landsat-based time series land cover and meta-analysis derived habitat preferences. Landscape Ecology. 2025;40.\u003c/li\u003e\n\u003cli\u003eHuang C, Li X, Khanal L, Jiang X. Habitat suitability and connectivity inform a co-management policy of protected area network for Asian elephants in China. PeerJ. 2019;7:e6791.\u003c/li\u003e\n\u003cli\u003eWang J, Li X, Duan W, Tian Y, Han R, Meng D, et al. Multi-scale habitat selection and constraints of a small Asian elephant population in Yunnan Nangunhe National Nature Reserve, China. Global Ecology and Conservation. 60:e03616.\u003c/li\u003e\n\u003cli\u003eChatziandreou N, Stock N, Young D, Andrejeva J, Hagmaier K, McGeoch D, et al. Relationships and host range of human, canine, simian and porcine isolates of simian virus 5 (parainfluenza virus 5). The Journal of general virology. 2004;85:3007-16.\u003c/li\u003e\n\u003cli\u003eZhai J, Zhai S, Lin T, Liu J, Wang H, Li B, et al. First complete genome sequence of parainfluenza virus 5 isolated from lesser panda. Archives of Virology. 2017;162:1413-1418.\u003c/li\u003e\n\u003cli\u003eXie J, Tong P, Zhang A, Zhang L, Song X, Kuang L. Identification and Characterization of the First Equine Parainfluenza Virus 5. Virologica Sinica. 2020;35:245-247.\u003c/li\u003e\n\u003cli\u003eSchoch CL, Ciufo S, Domrachev M, Hotton CL, Kannan S, Khovanskaya R, et al. NCBI Taxonomy: a comprehensive update on curation, resources and tools. Database (Oxford). 2020;2020:baaa062.\u003c/li\u003e\n\u003cli\u003eCampos‐Arceiz A, de la Torre JA, Wei K, Wu XO, Zhu Y, Zhao M, et al. The return of the elephants: How two groups of dispersing elephants attracted the attention of billions and what can we learn from their behavior. Conservation Letters. 2021;14.\u003c/li\u003e\n\u003cli\u003eBai D, Wan XR, Zhang L, Campos-Arceiz A, Wei FW, Zhang ZB. The recent Asian elephant range expansion in Yunnan, China, is associated with climate change and enforced protection efforts in human-dominated landscapes. Frontiers in Ecology and Evolution. 2022;10.\u003c/li\u003e\n\u003cli\u003eLi L-L, Wang Q-Y, Yang H-P, Tao Y-X, Wang L-X, Yang Z-B, et al. Mobile animals and immobile protected areas: improving the coverage of nature reserves for Asian elephant conservation in China. Oryx. 57:532-539.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-microbiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mcro","sideBox":"Learn more about [BMC Microbiology](http://bmcmicrobiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/mcro","title":"BMC Microbiology","twitterHandle":"#bmcmicrobiology","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Asian elephant, Gut microbiome, Metagenomics, Movement, Environmental exposure, Conservation biology","lastPublishedDoi":"10.21203/rs.3.rs-8699565/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8699565/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e[Background] Rapid changes can affect gut microbiome of animals. Wild Asian elephants (\u003cem\u003eElephas maximus\u003c/em\u003e) are poorly studied, and the 2021 northward movement of a Yunnan wild Asian elephant herd is a natural experiment to explore how long distance movement affects gut microbiome of endangered animals.\u003c/p\u003e\n\u003cp\u003e[Methods] Metagenomics was used to compare fecal samples of long distance movement herd (KM), short distance groups with different geographic relationships (JH,MH) and stable group (CY). The objective was to evaluate the effect of scale of movement on the gut communities in wild Asian elephants.\u003c/p\u003e\n\u003cp\u003e[Results] Long distance movement caused significant changes in gut microbiota.Compared to JH group, KM group showed a significant decrease in gut microbiota (P \u0026lt; 0.05) and changes in gut microbiota (higher community structure) with more heterogeneity between individuals. Key taxa showed higher abundances of environmentally sourced bacteria (Burkholderia), dominant methanogenic archaea (Methanobrevibacter) and a distinct virome (Virome) in the KM group, which was sensitive to habitat changes. For the first time \u003cem\u003eOrthorubulavirus mammalis\u003c/em\u003e (zoonotic risk) was detected in the KM group due to cross host virus transmission.\u003c/p\u003e\n\u003cp\u003e[Conclusion] This study show that long-distance movement can change the gut microbiome of wild Asian elephants. The costs of environmental exposure may be incurred and metabolic adaptation may also be signalled. The virome could be used as a biomarker of environmental changes in Asian elephants, warranting further investigation with larger samples. This shows that gut microbiome monitoring may be critical for future health studies and conservation management for wild Asian elephants.\u003c/p\u003e","manuscriptTitle":"Metagenomic insights into the Impact of Long-Distance Movement on the gut microbiota of wild Asian elephants","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-13 17:09:37","doi":"10.21203/rs.3.rs-8699565/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-03-19T06:42:40+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-09T07:11:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"295195698739567666557145066928322199744","date":"2026-02-23T09:56:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"124364796147294178935093917348947475143","date":"2026-02-09T09:01:19+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-08T08:54:10+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-06T12:12:36+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-06T11:46:54+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Microbiology","date":"2026-02-06T11:00:13+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-microbiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mcro","sideBox":"Learn more about [BMC Microbiology](http://bmcmicrobiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/mcro","title":"BMC Microbiology","twitterHandle":"#bmcmicrobiology","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"02ef3d9b-bc94-4d23-82d8-42c801b6428f","owner":[],"postedDate":"February 13th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-02-13T17:09:37+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-13 17:09:37","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8699565","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8699565","identity":"rs-8699565","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}