{"paper_id":"190c2bc0-a6ad-4a8c-9107-44f6a7a4c2e2","body_text":"Location matters: variations in gut microbiota composition of spatially separated freshwater turtles | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Location matters: variations in gut microbiota composition of spatially separated freshwater turtles T. Franciscus Scheelings, Thi Thu Hao Van, Robert J. Moore, Lee F. Skerratt This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4445807/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background The gut microbiota of vertebrates is malleable and may be shaped by both intrinsic and extrinsic factors. Here, the effect that geography has on the gut microbiota of two species of Australian freshwater chelonians, eastern longneck turtle ( Chelodina longicollis ) and Macquarie River turtle ( Emydura macquarii ), captured from waterbodies with different levels of anthropogenic pressure was investigated. We analysed the microbiota composition, structure and diversity through 16S rRNA gene amplicon sequencing. It was hypothesized that animals from less disturbed environments would harbour a more diverse gut microbial population. Results The gut microbiotas from 93 turtles ( C. longicollis n = 78; E. macquarii n = 15), from five locations, were analysed. For both species the most predominant phylum was Proteobacteria . Gut microbiota alpha diversity varied significantly between the C. longicollis from all locations, but no differences were found for E. macquarii . In C. longicollis , turtles from wetlands within the centre of Melbourne had the lowest alpha diversity metrics, while the highest alpha diversity values were seen in turtles captured from an undisturbed rural waterbody. Beta diversity, obtained by weighted UniFrac distance, showed significant differences between location of capture for both species of turtles in this investigation. For C. longicollis , 91 biomarkers were identified responsible for explaining differences between locations, and in E. macquarii 40 biomarkers were found. Core community analysis revealed 49 and 36 ASVs shared between populations of C. longicollis and E. macquarii respectively. Conclusions The study showed that gut microbiota composition of freshwater turtles was significantly influenced by locality and that the disrupted environments may reduce microbial diversity in C. longicollis . The results highlight the need to interpret chelonian microbiota data in the context of geography and human disturbance of the environment. Chelonian eastern longneck turtle freshwater turtle location Macquarie River turtle microbiota Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Background Residing on, and within all vertebrates is a diverse array of microorganisms which play a key role in host adaptation. Known as the microbiota, specific combinations of microbial inhabitants may confer teleological advantages or disadvantages to animals and are critical in determining health and behaviour [ 1 ]. Such is their importance to normal homeostasis, the host and its associated microbiota can be thought of as a metaorganism [ 2 ], in which millions of genes are working synergistically to drive physiological function and evolution [ 3 ]. Understanding these complex relationships is an exciting emerging field in the biological sciences, however, a thorough comprehension of vertebrate-microbiota interactions is currently hampered by a taxonomic bias in the breadth of investigations. Overwhelmingly, mammals are the group of animals most frequently targeted for microbiota research, with comparatively few investigations in the other vertebrate classes [ 4 ]. Microbiota research in wild freshwater chelonians is particularly depauperate, with only a handful of studies that have explored the microbial populations in this important clade [ 5 – 11 ]. Chelonians are among the most imperilled species on the planet [ 12 – 14 ], and in Australia, nearly half of the described freshwater species are listed as threatened [ 15 ]. Threats to global turtle populations include habitat loss, over-harvesting, pollution, poaching, and emerging novel diseases [ 16 – 18 ]. Importantly, these pressures have been implicated in a decrease in microbiota diversity in a range of species, with potential deleterious implications to host physiology [ 19 – 21 ]. Given the importance of the microbiota in metaorganism health, preservation of natural microbiotas should be a significant focus of conservation efforts [ 22 ]. The gut microbiotas of animals are malleable and may be influenced by a range of factors, two of which are locality and habitat disturbance. Anthropogenic-mediated environmental change has been shown to adversely affect the gut microbiotas of primates with negative consequences for digestive efficiency in some [ 23 – 27 ]. However, habitat disturbance does not explain all observed differences in microbiotas of vertebrates, as local environmental factors unrelated to environmental degradation have been implicated in shaping the microbial populations of geographically distinct populations of Australian sea lions ( Neophoca cinerea ) [ 28 ], loggerhead turtles ( Caretta caretta ) [ 29 ], and Aotearoa New Zealand takahē ( Porphyrio hochstetteri ) [ 30 ]. The factors that sculpt microbial inhabitation of vertebrate hosts are likely many and complex but understanding them is critical to unravelling niche occupancy, plasticity and health in animals. Preliminary investigations have begun to discover how freshwater turtle microbiotas respond to environmental stressors [ 6 , 31 ], but further research is required in this field. The aims of this study were to expand our knowledge on microbiotas of freshwater chelonians and explore how location and differences in habitat quality can influence microbial assemblage in these species. To achieve this, the gut microbiotas of two species of turtle: eastern longneck turtle ( Chelodina longicollis ), and Macquarie River turtle ( Emydura macquarii ), in multiple geographically distinct field sites across Victoria, Australia were investigated. Except for the pig-nosed turtle ( Carettochelys insculpta ), all Australian freshwater turtles belong to the family Chelidae , and are characterised by being pleurodirus. Additionally, their forelimbs and hindlimbs are jointed and not paddle-shaped, they have distinct ankle-joints, and their feet are webbed with either four or five-claws [ 32 ]. The longneck turtle is a common species found throughout eastern Australia and occupies a broad range of freshwater habitats. They are opportunistic predators and are capable of long distance overland migrations [ 33 ]. The Macquarie River turtle is a short-necked species inhabiting larger rivers within the Murray-Darling River system and associated drainages west of the Great Dividing Range in south-eastern Australia, as well as coastal rivers in mid-eastern Australia [ 32 ]. They are opportunistically omnivorous, with the majority of their diet comprising filamentous algae and plant detritus, and the remainder consisting of vertebrate carrion and aquatic invertebrates [ 34 ]. Both species frequently inhabit the same waterbodies sympatrically, where their ranges overlap. The Macquarie River turtle is listed as threatened in Victoria due to continued population declines over the last three decades [ 35 ]. Our data explore how geography influences gut microbiotas in free-ranging freshwater turtles and will provide valuable insights into the chelonian-microbiota relationship thus aiding in directing future research endeavours. Methods Study populations Turtles were trapped from multiple waterbodies in Victoria, Australia, in the Austral summer of 2022/23. Field sites included a mixture of waterbodies in both urban and rural areas, as well as ponds located within a sewerage treatment facility (Fig. 1 ). Rural waterbodies included Maloney’s Wetland (MW, -36.102589, 146.872034) which is a naturally occurring creek system, and Barnawatha (BW, -36.0999377, 146.6240912) which was originally man-made as a waste-water treatment plant but was abandoned to rewilding nearly a decade ago. Urban waterbodies included Duck Pond (DP, -37.7732825, 145.0348189) and Ivanhoe Wetland (IW, -37.7734116, 145.0354874), within the Darebin Parklands, in Alphington, Melbourne. Melbourne is the second largest city in Australia with a population of approximately 4.9 million people. DP is an old landfill site that became a permanent waterbody 40 years ago, and IW is a manmade wetland constructed during the early 1990s and is closely associated with the Darebin Creek system. DP and IW are separated by approximately 200m in a straight line. The sewerage treatment ponds were located within the Baranduda Wastewater Treatment Plant (BD, -36.1527907, 146.9600324) in Baranduda and are completely artificial. Sample collection At all sites, turtles were trapped using large, 6 hoop fyke nets with 28mm black, knotless mesh and a 2.5m wing with a 48cm drop and baited with chunks of lamb or chicken liver. Six to 10 nets were placed into each waterbody and left overnight. In the morning, traps were brought back to shore and turtles removed for sample collection. In Darebin Parklands (DP and IW), trapping only occurred for a single night at each site, and for all other locations traps were set for 2–3 nights. Once turtles had been removed from the nets, they were placed into dorsal recumbency, and a cotton swab was inserted into the cloaca and twirled so that it contacted the cloacal mucosa. The swab was then retracted, and the tip cut using flame-sterilised wire cutters and stored in 1ml of ZymoBIOMICS DNA/RNA Shield (Integrated Sciences) in a sterile Eppendorf tube. The Eppendorf tubes were then frozen and stored at -80°C until DNA extraction could occur. All turtles were released alive at their point of capture following sample collection. DNA extraction DNA was extracted using the ZymoBIOMICS DNA Miniprep Kit (Integrated Sciences) according to the manufacturer’s instructions. Following extraction, DNA was stored at -80°C until amplicon sequencing could take place. 16S rRNA gene amplicon sequencing The V3-V4 region of 16S rRNA genes were PCR amplified with forward primer 5’ ACTCCTACGGGAGGCAGCAG 3’ and reverse primer 5’ GGACTACHVGGGTWTCTAAT 3’ using Q5 high fidelity polymerase (New England Biolabs) with a dual barcoding strategy [ 36 ]. The PCR cycling parameters were, 98°C for 1 minute, 35 cycles of 98°C for 10 seconds, 49°C for 30 seconds, and 72°C for 30 seconds, followed by a 10-minute extension at 72°C. Sequencing was performed on an Illumina MiSeq system (2 x 300 bp). Data processing Sequence data was analysed using Quantitative Insights into Microbial Ecology 2 (QIIME2) version 220.6 [ 37 ], using the Divisive Amplicon Denoising Algorithm (DADA2) plugin for quality filtering, denoising, chimaera detection, and amplicon sequence variant (ASV) calling [ 38 ]. ASVs were taxonomically classified using the SILVA database (v138.1) [ 39 ]. An ASV abundance table with taxonomic assignments was produced for further analysis. Statistical analyses ASV abundance data was analysed in R, utilising the package ‘phyloseq’ [ 40 ]. Sequencing depth was explored using rarefaction curves and then data was rarefied to an even depth of 1500 reads. Alpha diversity was explored using Observed ASVs, Shannon index and Chao1 estimates. Alpha diversity was tested for normality using the Shapiro-Wilks test for each species. In longnecks, Observed (W = 0.91, p < 0.01), Chao1 (W = 0.91, p < 0.01), and Shannon (W = 0.96, p = 0.02), were all non-normally distributed and therefore comparisons were first made using the Kruskal-Wallis test, and then paired comparisons between groups were made using the pairwise Wilcoxon rank-sum test. For Macquarie River turtles Observed (W = 0.91, p = 0.15), Chao1 (W = 0.91, p = 0.15) and Shannon diversity (W = 0.94, p = 0.44) were all normally distributed and so comparisons were made between groups using a Welch two sample t-test. For both species beta diversity was investigated using Principal Co-ordinate Analysis (PCoA) on weighted UniFrac distances and Adonis tests to compare all locations within species, and then pairwise comparisons were made between all combinations of locations. Where variances between locations were found, we explored differentially abundant taxa using Linear discriminant analysis Effect Size (LEfSe) and LDA plots (cut-off value of 3) with the package ‘microbiomeMarker’ [ 41 ]. The core microbiota was determined for each species by setting a prevalence threshold of 50% and a detection level of 0.05 and was represented using heat maps. For all pairwise tests, p-values were adjusted for multiple comparisons with Benjamini-Hochberg (BH) correction. For all statistical analyses significance was accepted if p < 0.05. Results In total, 93 turtles were captured and sampled. At MW we captured 8 turtles comprised of a single species (Macquarie River turtle), at BW we captured 18 turtles of a single species (eastern longneck turtle), at BD we captured 27 turtles comprised of 2 species (eastern longneck turtle n = 20, Macquarie River turtle n = 7), and at DP and IW we captured 20 in each pond, of a single species (eastern longneck turtle). A total of 1,737,515 sequences were generated after quality checking and removal of chimaeras, giving an average of 18,683 sequences per sample. The taxonomic breakdown of sequence data yielded 29 bacterial phyla, 60 classes, 161 orders, 255 families, 415 genera, and 315 species. Eastern longneck turtle The five most predominate phyla were Proteobacteria (39%), Actinobacteriota (26.9%), Deinococcota (8.57%), Bacteroidota (7.74%), and Firmicutes (5.25%) (Fig. 2 A), and the five most abundant families were Comamonadaceae (18.1%), Intrasporangiaceae (10.9%), Deinococcaceae (9.5%), Rhodocyclaeceae (6.05%), and Leptospiraceae (4.27%) (Fig. 2 B). Analysis of alpha diversity revealed that there were significant differences between localities for Observed ASVs (χ² = 19.35, df = 3, p < 0.01), Chao1 (χ² = 19.35, df = 3, p < 0.01), and Shannon diversity (χ² = 25.94, df = 3, p < 0.01) (Fig. 3 A). These observations were consistent when all samples were analysed in entirety, as well as for pairwise comparisons between certain combinations of locations (Additional file 1). For beta diversity we detected differences between locations when samples were analysed together (df = 3, SS T = 4.56, R 2 = 0.34, f.model = 12.63, p < 0.01) (Fig. 4 A). Differences existed between all combinations of locations when pairwise comparisons, with BH correction of p-values, were done (Additional file 1). LefSe analysis between locations revealed 91 significant biomarkers between groups with 19 of these found in animals from IW, 24 from DP, 23 from BW, and 25 from BD (Fig. 5 A). For core microbiota 49 ASVs met the selection criteria (Fig. 6 A). Macquarie River turtle The five most predominate phyla were Proteobacteria (32.1%), Deinococcota (24.5%), Bacteroidota (21.2%), Actinobacteriota (12.8%), and Cyanobacteria (6.12%) (Fig. 2 c), and the five most abundant families were Deinococcaceae (26.2%), Comamonadaceae (23.8%), Weeksellaceae (17.3%), Nostocaceae (3.94%), and Flavobacteriaceae (2.16%) (Fig. 2 d). Analysis of alpha diversity revealed that there were no significant differences between localities for Observed ASVs (t=-0.02, df = 11.83, p = 0.98), Chao1 (t=-0.02, df = 11.83, p = 0.98), and Shannon diversity (t=-0.29, df = 9.11, p = 0.78) (Fig. 3 b). Conversely, for beta diversity we detected a significant difference between locations (df = 1, SS T = 0.35, R 2 = 0.14, f.model = 2.16, p = 0.03) (Fig. 4 b). LefSe analysis between locations revealed 40 significant biomarkers between groups with 13 of these found in MW, and 27 found in BD (Fig. 5 b). For core microbiotae 36 ASVs met the selection criteria (Fig. 6 B). Discussion In this study the gut microbiota composition in two species of Australian freshwater chelonians, the eastern longneck turtle and the Macquarie River turtle, are described. We found that in both species the predominant phylum was Proteobacteria , followed by Actinobacteriota , Deinococcota , Bacteroidota , and Firmicutes in the eastern longneck, and Deinococcota , Bacteroidota , Actinobacteriota , and Cyanobacteria in Macquarie River turtles. There is considerable variability of gut microbiota composition in chelonians, with Proteobacteria dominating in other species such as map turtles ( Graptemys pseudogeographica ) [ 9 , 11 ], wild Beal’s eyed turtles ( Sacalia bealei ) [ 8 ], and also in all species of female sea turtles that were sampled during nesting [ 42 ]. However, Firmicutes has been reported as the most prevalent phylum in other chelonians including Seychelles giant tortoises ( Aldabrachelys gigantea ) [ 43 ], southern river terrapins ( Batagur affinis ) [ 7 ], captive Beal’s eyed turtles [ 8 ], painted turtles ( Chrysems picta ) [ 10 ], one population of flatback turtles ( Natator depressus ) [ 29 ], and a range of sea turtles under different age, sex and health classes [ 44 ]. Interestingly, a predominance of Firmicutes was also seen in Macquarie River turtles captured from undisclosed waterways in Queensland, Australia [ 6 , 31 ]. Making meaningful comparisons between studies to explain observed variance is difficult as microbiota investigations are complicated by differences in methodology [ 45 ], phylogenetic history of species sampled [ 42 ], physiological state of hosts [ 46 ], and local environmental factors [ 47 ]. Therefore, until protocols to standardise field and laboratory practices have been agreed upon, caution should be taken when inferring which factors have physiological effects on microbiota based on differences between studies. This investigation into the gut microbiota in freshwater chelonians has shown that bacterial communities differ significantly among turtles of the same species but originating from geographically distinct populations. These differences were apparent in both composition and diversity and highlight the importance of interpreting microbiota data in the context of locality. Geography has been shown to play a key role in driving gut microbial ecology in vertebrate hosts and is likely to be related to deterministic processes such as food availability, inter/intraspecific competition, host dispersal and local environmental factors [ 48 – 51 ]. However, these findings are not consistent across all vertebrate classes with location not an important factor in determining microbiota composition in eastern garter snakes ( Thamnophis sirtalis sirtalis ) and northern watersnakes ( Neridia sipedon sipedon ) [ 52 ]. Correctly identifying the processes responsible for observed disparities between populations of wild animals is difficult because how microorganisms colonise the gut of vertebrates is multifaceted and dependent on a suite of host, microbe, and spatial ecology features. Differences in alpha diversity metrics existed for all populations of eastern longneck turtles. A consistent finding was that animals from urban ponds in the middle of Melbourne (DP and IW) scored lowest for all alpha diversity measures in comparison to the other study locations (Fig. 3 A). These observations were particularly apparent in animals captured from DP, in which Observed ASVs, Chao1 and Shannon diversity were all much lower than the other localities. Both DP and IW are in areas of high public visitation and there may be significant public interaction with the animals at these sites. Interestingly, animals captured from the wastewater treatment plant at BD had higher alpha diversity metrics than both DP and IW. The ponds at BD are all manmade and constructed of concrete, there is no vegetation surrounding or within the ponds, and given that it is a facility used for processing human waste it would be easy to assume that this was the most disturbed habitat that we captured turtles. Human interaction with turtles is lower at BD than at DP and IW and only occurs when maintenance of the treatment ponds is necessary. Turtles from BW had the highest alpha diversity scores, and this was the least disturbed habitat with almost no human visitation. For longneck turtles it appears that presence of humans may be a more significant factor in reducing microbiota richness and diversity than habitat quality. Anthropogenic pressures have been shown to considerably alter gut microbiota of a range of wildlife including Tome’s spiny rats ( Proechimys semispinosus ) [ 53 ], swan geese ( Anser cygnoides ) [ 54 ], Kuhl’s pipistrelle bats ( Pipistrellus kuhlii ) [ 20 ], and olive baboons ( Papio anubis ) [ 55 ], and there are concerns that these disturbances in microbial ecology may have negative implications for vertebrate conservation [ 22 , 56 ]. In contrast to eastern longneck turtles, no significant differences in alpha diversity due to location were found for Macquarie River turtles and it is possible that specific physiological traits, such as omnivory, in this species ensures a more stable environment for gut microbiotas. The role that diet may be playing in driving differences in bacterial composition in our samples is unknown. Eastern longneck turtles are obligate carnivores that appear to have limited dietary preferences and will feed on almost any vertebrate or invertebrate that they can apprehend and subdue [ 57 , 58 ]. In contrast, the Macquarie River turtle is omnivorous with much of their diet consisting of filamentous algae supplemented with carrion when available [ 34 , 59 ]. Given the relative dietary plasticity seen in both of these species, geographic variation in food consumption likely results from local differences in prey abundance and this may be a significant factor in shaping gut microbiota composition. Other influences on dietary intake in Australian freshwater turtles are competition with fish [ 57 ], and inter-species antagonism with other chelonians [ 35 ]. In this investigation we made no attempt to assess food availability or heterospecific behaviour and therefore their roles in resource partitioning and as a determinant of microbial community composition remains unknown. One further potentially significant confounder on gut microbiotas is “Good Samaritan” feeding of turtles in public places. While this practice was not directly observed during trapping events, feeding of wildlife is common in Melbourne [ 60 ], and access to anthropogenic food sources has been shown to negatively impact the gut microbiotas of multiple vertebrate species [ 55 , 61 , 62 ]. An interesting finding in this investigation was the significant differences in both alpha and beta diversity between longneck turtles originating from ponds in the Darebin Parklands. These ponds are separated by approximately 200m in a straight line which should not be a significant obstacle for this species to overcome. Eastern longneck turtles are capable of long terrestrial migrations to escape unfavourable conditions [ 63 , 64 ], made possible by their resistance to desiccation [ 65 ]. The results of this study may indicate that there is little seasonal fluctuation in resources available to turtles within these ponds negating the need for individuals to emigrate between waterbodies. In the event that turtles do translocate to new ponds, if and how long gut microbiotas take to assimilate to their new environments remains unknown. For both species sampled, the bacterial family Comamonadaceae was routinely identified in almost all samples. These bacteria form a major group of the Beta-Proteobacteria and are characterised as being poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV)-degrading denitrifying bacteria frequently isolated from sewerage sludge [ 66 ]. This result is not surprising given that many of our turtles originated from either active, or decommissioned sewerage and wastewater treatment plants. What is unclear is if these bacteria form a normal component of the gut microflora in these turtles, or if they are simply environmental species that have been inadvertently sequenced. However, we did identify this family in animals originating from MW, which is a natural waterbody with no history of use as a wastewater treatment facility, and they have also been identified as normal flora in a range of vertebrates including fish, birds and humans [ 67 – 69 ]. Further exploration of turtles from more pristine waterways is warranted to determine the prevalence of this bacterial family in chelonians, and its significance to turtle physiology. Conclusions The analysis of the bacterial microbiota of wild freshwater chelonians indicated that microbial communities differ significantly among individuals of the same species that originate from different populations. This finding highlights the importance of interpreting microbiota data in the context of environment, as it appears that local effects significantly alter microbial composition in chelonians. Of particular interest was the differences observed between turtles from DP and IW given their proximity. Eastern longneck turtles are known to undergo long terrestrial sojourns and thus it is possible that there is movement of individuals between these ponds. If this does occur, then it suggests gut microbiotas assimilate to local conditions but how long this takes is unknown at this stage, and future research should be aimed at determining plasticity of gut microbiotas in individual turtles. Abbreviations ASV Amplicon sequence variant BD Baranduda BW Barnawatha DNA Deoxyribonucleic acid DP Duck Pond IW Ivanhoe Wetland MW Maloney’s Wetland NCBI National Centre for Biotechnology Information PCoA Principal coordinate analysis rRNA Ribosomal ribonucleic acid. Declarations Ethics approval This study was approved by The University of Melbourne Office of Research Ethics and Integrity (Ethics ID: 2022-24808-32226-4) and all experiments were performed in accordance with relevant guidelines and regulations. Turtles were trapped and sampled under permit 10010480 from the Department of Environment, Land, Water and Planning, and permit number RP1497 from the Victorian Fisheries Authority. All turtles were released alive at their point of capture immediately after sampling had been completed. Competing interests The authors declare that they have no competing interests. Funding TFS is supported by a McKenzie Postdoctoral Fellowship at the University of Melbourne. Authors’ contributions TFS was responsible for experimental design, collecting samples and analysing and interpreting data. RJM and TTHV were responsible for16S rRNA gene amplicon production and sequencing, bioinformatics, and data interpretation. All authors were major contributors in writing the manuscript and have approved the final document. Availability of data and materials All data presented here and in the supplementary material have been submitted to The National Center for Biotechnology Information (www.ncbi.nlm.nih.gov) and can be accessed under accession number xxx Acknowledgments We thank James Van Dyke, Donald McKnight, Angela Simms, Tilli Beaumont, Emma Kynaston, Peter Wiltshire, Kim Davis, Dan Guinto and Jasper White for assistance in placing traps and processing turtles. References Peixoto RS, Harkins DM, Nelson KE. Advances in microbiome research for animal health . Annu Rev Anim Biosci 2021, 9 : 289-311. Bosch TC, McFall-Ngai MJ. Metaorganisms as the new frontier . Zoology (Jena) 2011, 114 : 185-190. Bordenstein SR, Theis KR. Host biology in light of the microbiome: ten principles of holobionts and hologenomes . PLoS Biol 2015, 13 : e1002226. Colston TJ, Jackson CR. 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McMurdie PJ, Holmes S. phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data . PLoS One 2013, 8 : e61217. Cao Y, Dong Q, Wang D, Zhang P, Liu Y, Niu C. microbiomeMarker: an R/Bioconductor package for microbiome marker identification and visualization . Bioinformatics 2022, 38 : 4027-4029. Scheelings TF, Moore RJ, Van TTH, Klaassen M, Reina RD. Microbial symbiosis and coevolution of an entire clade of ancient vertebrates: the gut microbiota of sea turtles and its relationship to their phylogenetic history . Anim Microbiome 2020, 2 : 17. Sandri C, Correa F, Spiezio C, Trevisi P, Luise D, Modesto M, Remy S, Muzungaile MM, Checcucci A, Zaborra CA, Mattarelli P. Fecal microbiota characterization of Seychelles giant tortoises ( Aldabrachelys gigantea ) living in both wild and controlled environments . Front Microbiol 2020, 11 : 569249. Kuschke SG. What lives on and in the sea turtle? A literature review of sea turtle bacterial microbiota . Anim Microbiome 2022, 4 : 52. Bartolomaeus TUP, Birkner T, Bartolomaeus H, Lober U, Avery EG, Mahler A, Weber D, Kochlik B, Balogh A, Wilck N, et al. Quantifying technical confounders in microbiome studies . Cardiovasc Res 2021, 117 : 863-875. Stothart MR, Palme R, Newman AEM. It's what's on the inside that counts: stress physiology and the bacterial microbiome of a wild urban mammal . Proc R Soc B 2019, 286 : 20192111. White J, Amato KR, Decaestecker E, McKenzie VJ. Editorial: Impact of anthropogenic environmental changes on animal microbiomes . Front Ecol Evol 2023, 11. Pan B, Han X, Yu K, Sun H, Mu R, Lian CA. Geographical distance, host evolutionary history and diet drive gut microbiome diversity of fish across the Yellow River . Mol Ecol 2023, 32 : 1183-1196. Mason B, Petrzelkova KJ, Kreisinger J, Bohm T, Cervena B, Fairet E, Fuh T, Gomez A, Knauf S, Maloueki U, et al. Gastrointestinal symbiont diversity in wild gorilla: A comparison of bacterial and strongylid communities across multiple localities . Mol Ecol 2022, 31 : 4127-4145. Joakim RL, Irham M, Haryoko T, Rowe KMC, Dalimunthe Y, Anita S, Achmadi AS, McGuire JA, Perkins S, Bowie RCK. Geography and elevation as drivers of cloacal microbiome assemblages of a passerine bird distributed across Sulawesi, Indonesia . Anim Microbiome 2023, 5 : 4. Wasimuddin, Malik H, Ratovonamana YR, Rakotondranary SJ, Ganzhorn JU, Sommer S. Anthropogenic disturbance impacts gut microbiome homeostasis in a Malagasy primate . Front Microbiol 2022, 13 : 911275. Dallas JW, Meshaka WE, Jr., Zeglin L, Warne RW. Taxonomy, not locality, influences the cloacal microbiota of two nearctic colubrids: a preliminary analysis . Mol Biol Rep 2021, 48 : 6435-6442. Fackelmann G, Gillingham MAF, Schmid J, Heni AC, Wilhelm K, Schwensow N, Sommer S. Human encroachment into wildlife gut microbiomes . Commun Biol 2021, 4 : 800. Wu Y, Yang Y, Cao L, Yin H, Xu M, Wang Z, Liu Y, Wang X, Deng Y. Habitat environments impacted the gut microbiome of long-distance migratory swan geese but central species conserved . Sci Rep 2018, 8 : 13314. Moy M, Diakiw L, Amato KR. Human-influenced diets affect the gut microbiome of wild baboons . Sci Rep 2023, 13 : 11886. West AG, Waite DW, Deines P, Bourne DG, Digby A, McKenzie VJ, Taylor MW. The microbiome in threatened species conservation . Biol Conserv 2019, 229 : 85-98. Chessman B. Food of the snake-necked turtle, Chelodina Longicollis (Shaw) (Testudines: Chelidae) in the Murray Valley, Victoria and New South Wales . Wildl Res 1984, 11 : 573-578. Georges A, Norris RH, Wensing L. Diet of the freshwater turtle Chelodina longicollis (Testudines: Chelidae) from the coastal dune lakes of the Jervis Bay territory . Aust Wildl Res 1986, 13 : 301-308. Spencer R-J, Thompson MB, Hume ID. The diet and digestive energies of an Australian short-necked turtle, Emydura macquarii . Comp Biochem Physiol Part A 1998, 121 : 341-349. McLees B. Feeding wildlife right or wrong? Community attitudes towards feeding wildlife in Melbourne Australia, and implications for management. Deakin University, School of Ecology and Environment; 2000. Sugden S, Sanderson D, Ford K, Stein LY, St Clair CC. An altered microbiome in urban coyotes mediates relationships between anthropogenic diet and poor health . Sci Rep 2020, 10 : 22207. Gillman SJ, McKenney EA, Lafferty DJR, Moore B. Human-provisioned foods reduce gut microbiome diversity in American black bears ( Ursus americanus ) . J Mammal 2022, 103 : 339-346. Kennett RM, Georges A. Habitat utilization and its relationship to growth and reproduction of the eastern long-necked turtle, Chelodina longicollis (Testudinata: Chelidae), from Australia . Herpetologica 1990, 46 : 22-33. Graham T, Georges A, McElhinney N. Terrestrial orientation by the eastern long-necked turtle, Chelodina longicollis , from Australia . J Herpetol 1996, 30 : 467-477. Chessman BC. Evaporative water loss from three south-eastern Australian speices of freshwater turtle . Aust J Zool 1984, 32 : 649-655. Khan ST, Horiba Y, Yamamoto M, Hiraishi A. Members of the family Comamonadaceae as primary poly(3-hydroxybutyrate-co-3-hydroxyvalerate)-degrading denitrifiers in activated sludge as revealed by a polyphasic approach . Appl Environ Microbiol 2002, 68 : 3206-3214. Gajardo K, Rodiles A, Kortner TM, Krogdahl A, Bakke AM, Merrifield DL, Sorum H. A high-resolution map of the gut microbiota in Atlantic salmon ( Salmo salar ): a basis for comparative gut microbial research . Sci Rep 2016, 6 : 30893. Yang Y, Deng Y, Cao L. Characterising the interspecific variations and convergence of gut microbiota in Anseriformes herbivores at wintering areas . Sci Rep 2016, 6 : 32655. Aguirre de Carcer D, Cuiv PO, Wang T, Kang S, Worthley D, Whitehall V, Gordon I, McSweeney C, Leggett B, Morrison M. Numerical ecology validates a biogeographical distribution and gender-based effect on mucosa-associated bacteria along the human colon . ISME J 2011, 5 : 801-809. Additional Declarations No competing interests reported. Supplementary Files AdditionalFile1.docx Additional File 1 Pairwise Wilcoxon rank sum test comparisons between eastern longnecks for Alpha diversity metrics. Numbers represent corrected (BH) p -values for multiple comparisons. Significant values are indicated by bold text. Table S1. Pairwise Wilcoxon rank sum test comparisons between longnecks for Observed ASVs. Numbers represent corrected (BH) p-values for multiple comparisons. Significant values are indicated by bold text. Table S2. Pairwise Wilcoxon rank sum test comparisons between longnecks for Chao1. Numbers represent corrected (BH) p -values for multiple comparisons. Significant values are indicated by bold text. Table S3. Pairwise Wilcoxon rank sum test comparisons between locations for Shannon diversity. Numbers represent corrected (BH) p -values for multiple comparisons. Significant values are indicated by bold text. Table S4. Pairwise adonis test comparisons between locations for beta diversity. Numbers represent corrected (BH) p -values for multiple comparisons. Significant values are indicated by bold text. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-4445807\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":true,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":308280392,\"identity\":\"a2577406-c62c-4703-9b16-5bfec2cf9608\",\"order_by\":0,\"name\":\"T. Franciscus Scheelings\",\"email\":\"data:image/png;base64,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\",\"orcid\":\"\",\"institution\":\"The University of Melbourne\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"T.\",\"middleName\":\"Franciscus\",\"lastName\":\"Scheelings\",\"suffix\":\"\"},{\"id\":308280393,\"identity\":\"6151483e-4d17-4246-bb51-06b63f680185\",\"order_by\":1,\"name\":\"Thi Thu Hao Van\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"RMIT University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Thi\",\"middleName\":\"Thu Hao\",\"lastName\":\"Van\",\"suffix\":\"\"},{\"id\":308280394,\"identity\":\"fd411b2f-be13-4858-ab6b-dbbf66e56dc8\",\"order_by\":2,\"name\":\"Robert J. Moore\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"RMIT University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Robert\",\"middleName\":\"J.\",\"lastName\":\"Moore\",\"suffix\":\"\"},{\"id\":308280395,\"identity\":\"f9eed054-fbcb-46c5-bd2a-62930a42aa9d\",\"order_by\":3,\"name\":\"Lee F. Skerratt\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"The University of Melbourne\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Lee\",\"middleName\":\"F.\",\"lastName\":\"Skerratt\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2024-05-19 23:23:49\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-4445807/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-4445807/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":57501182,\"identity\":\"e635c46a-660c-4139-a0d7-4d99dd27a0c8\",\"added_by\":\"auto\",\"created_at\":\"2024-05-31 13:57:52\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":424816,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eMap of Victoria, Australia, indicating location of trapping sites for turtles used in this investigation.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"image1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4445807/v1/d37f92110ac00352bc82d3dc.png\"},{\"id\":57500456,\"identity\":\"aa89ff0f-4e18-4c28-9803-b2c071230f2d\",\"added_by\":\"auto\",\"created_at\":\"2024-05-31 13:49:52\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":212457,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eStacked bar plot of relative abundance of (\\u003cstrong\\u003eA\\u003c/strong\\u003e) phyla in eastern longneck turtles (\\u003cem\\u003eChelodina longicollis\\u003c/em\\u003e) (n = 78), (\\u003cstrong\\u003eB\\u003c/strong\\u003e) 10 most common families in eastern longneck turtles (n = 78), (\\u003cstrong\\u003eC\\u003c/strong\\u003e) phyla in Macquarie River turtles (\\u003cem\\u003eEmydura macquarii\\u003c/em\\u003e) (n=15), and (\\u003cstrong\\u003eD\\u003c/strong\\u003e) 10 most common families in Macquarie River turtles (n=15). Samples are displayed along the bottom of the plots and location of capture is displayed at the top.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"image2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4445807/v1/5af388778611653a11d0dee2.png\"},{\"id\":57500450,\"identity\":\"f8a023bf-204e-4fc6-ac57-8dcd54087af9\",\"added_by\":\"auto\",\"created_at\":\"2024-05-31 13:49:52\",\"extension\":\"png\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":101398,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eAlpha diversity comparisons among trapping locations as displayed by boxplots for (\\u003cstrong\\u003eA\\u003c/strong\\u003e) eastern longneck turtles (\\u003cem\\u003eChelodina longicollis\\u003c/em\\u003e) (n = 78), and (\\u003cstrong\\u003eB\\u003c/strong\\u003e) Macquarie River turtles (\\u003cem\\u003eEmydura macquarii\\u003c/em\\u003e) (n=15). All animals were captured in Victoria, Australia in the Austral summer of 2022/23. Error bars represent SEM.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"image3.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4445807/v1/62809807190710483be296a9.png\"},{\"id\":57501706,\"identity\":\"14a50a1c-1498-4d85-8772-1409f4c9a641\",\"added_by\":\"auto\",\"created_at\":\"2024-05-31 14:05:52\",\"extension\":\"png\",\"order_by\":4,\"title\":\"Figure 4\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":116612,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eBeta diversity comparisons among trapping locations as displayed by principal co-ordinate analysis (PCoA) plot with UniFrac distances for (\\u003cstrong\\u003eA\\u003c/strong\\u003e) eastern longneck turtles (\\u003cem\\u003eChelodina longicollis\\u003c/em\\u003e) (n = 78), and (\\u003cstrong\\u003eB\\u003c/strong\\u003e) Macquarie River turtles (\\u003cem\\u003eEmydura macquarii\\u003c/em\\u003e) (n=15). All animals were captured in Victoria, Australia in the Austral summer of 2022/23.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"image4.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4445807/v1/fd540255909fdcaac31cb148.png\"},{\"id\":57500455,\"identity\":\"eef8543d-8fb3-4bb6-9c38-1a3208610c95\",\"added_by\":\"auto\",\"created_at\":\"2024-05-31 13:49:52\",\"extension\":\"png\",\"order_by\":5,\"title\":\"Figure 5\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":236387,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eLinear discriminant analysis (LDA) plot comparing differentially enriched taxa by trapping location for (\\u003cstrong\\u003eA\\u003c/strong\\u003e) eastern longneck turtles (\\u003cem\\u003eChelodina longicollis\\u003c/em\\u003e) (n = 78), and (\\u003cstrong\\u003eB\\u003c/strong\\u003e) Macquarie River turtles (\\u003cem\\u003eEmydura macquarii\\u003c/em\\u003e) (n=15). All animals were captured in Victoria, Australia in the Austral summer of 2022/23.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"image5.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4445807/v1/6e7e616180ba56252f2a81aa.png\"},{\"id\":57500453,\"identity\":\"b12f5f56-0da3-4deb-a63e-f1fbf5adeb5a\",\"added_by\":\"auto\",\"created_at\":\"2024-05-31 13:49:52\",\"extension\":\"png\",\"order_by\":6,\"title\":\"Figure 6\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":479184,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eThe core microbiota of cloacal samples from (\\u003cstrong\\u003eA\\u003c/strong\\u003e) eastern longneck turtles (\\u003cem\\u003eChelodina longicollis\\u003c/em\\u003e) (n = 78), and (\\u003cstrong\\u003eB\\u003c/strong\\u003e) Macquarie River turtles (\\u003cem\\u003eEmydura macquarii\\u003c/em\\u003e) (n=15). Heatmaps were created using a prevalence threshold of 50% and a detection level of 0.05.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"image6.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4445807/v1/26a56ad0021faf7cea2194cc.png\"},{\"id\":60432445,\"identity\":\"378c9bc2-97e1-4bf6-938b-6c74a5f68b9f\",\"added_by\":\"auto\",\"created_at\":\"2024-07-16 16:52:48\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":2151746,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4445807/v1/a9e92994-e58b-403f-9bb3-935368c99902.pdf\"},{\"id\":57502360,\"identity\":\"9124a67a-2148-48d0-87c1-3511879ac562\",\"added_by\":\"auto\",\"created_at\":\"2024-05-31 14:13:52\",\"extension\":\"docx\",\"order_by\":1,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":20870,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eAdditional File 1 \\u003c/strong\\u003ePairwise Wilcoxon rank sum test comparisons between eastern longnecks for Alpha diversity metrics. Numbers represent corrected (BH) \\u003cem\\u003ep\\u003c/em\\u003e-values for multiple comparisons. Significant values are indicated by bold text. \\u003cstrong\\u003eTable S1.\\u003c/strong\\u003e Pairwise Wilcoxon rank sum test comparisons between longnecks for Observed ASVs. Numbers represent corrected (BH) p-values for multiple comparisons. Significant values are indicated by bold text. \\u003cstrong\\u003eTable S2.\\u003c/strong\\u003e Pairwise Wilcoxon rank sum test comparisons between longnecks for Chao1. Numbers represent corrected (BH) \\u003cem\\u003ep\\u003c/em\\u003e-values for multiple comparisons. Significant values are indicated by bold text. \\u003cstrong\\u003eTable S3.\\u003c/strong\\u003e Pairwise Wilcoxon rank sum test comparisons between locations for Shannon diversity. Numbers represent corrected (BH) \\u003cem\\u003ep\\u003c/em\\u003e-values for multiple comparisons. Significant values are indicated by bold text. \\u003cstrong\\u003eTable S4. \\u003c/strong\\u003ePairwise adonis test comparisons between locations for beta diversity. Numbers represent corrected (BH) \\u003cem\\u003ep\\u003c/em\\u003e-values for multiple comparisons. Significant values are indicated by bold text.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"AdditionalFile1.docx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4445807/v1/5c944290acf46a4752de2b80.docx\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"Location matters: variations in gut microbiota composition of spatially separated freshwater turtles\",\"fulltext\":[{\"header\":\"Background\",\"content\":\"\\u003cp\\u003eResiding on, and within all vertebrates is a diverse array of microorganisms which play a key role in host adaptation. Known as the microbiota, specific combinations of microbial inhabitants may confer teleological advantages or disadvantages to animals and are critical in determining health and behaviour [\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e]. Such is their importance to normal homeostasis, the host and its associated microbiota can be thought of as a metaorganism [\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e], in which millions of genes are working synergistically to drive physiological function and evolution [\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e]. Understanding these complex relationships is an exciting emerging field in the biological sciences, however, a thorough comprehension of vertebrate-microbiota interactions is currently hampered by a taxonomic bias in the breadth of investigations. Overwhelmingly, mammals are the group of animals most frequently targeted for microbiota research, with comparatively few investigations in the other vertebrate classes [\\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e]. Microbiota research in wild freshwater chelonians is particularly depauperate, with only a handful of studies that have explored the microbial populations in this important clade [\\u003cspan additionalcitationids=\\\"CR6 CR7 CR8 CR9 CR10\\\" citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eChelonians are among the most imperilled species on the planet [\\u003cspan additionalcitationids=\\\"CR13\\\" citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e], and in Australia, nearly half of the described freshwater species are listed as threatened [\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e]. Threats to global turtle populations include habitat loss, over-harvesting, pollution, poaching, and emerging novel diseases [\\u003cspan additionalcitationids=\\\"CR17\\\" citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e]. Importantly, these pressures have been implicated in a decrease in microbiota diversity in a range of species, with potential deleterious implications to host physiology [\\u003cspan additionalcitationids=\\\"CR20\\\" citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e]. Given the importance of the microbiota in metaorganism health, preservation of natural microbiotas should be a significant focus of conservation efforts [\\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e22\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eThe gut microbiotas of animals are malleable and may be influenced by a range of factors, two of which are locality and habitat disturbance. Anthropogenic-mediated environmental change has been shown to adversely affect the gut microbiotas of primates with negative consequences for digestive efficiency in some [\\u003cspan additionalcitationids=\\\"CR24 CR25 CR26\\\" citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e27\\u003c/span\\u003e]. However, habitat disturbance does not explain all observed differences in microbiotas of vertebrates, as local environmental factors unrelated to environmental degradation have been implicated in shaping the microbial populations of geographically distinct populations of Australian sea lions (\\u003cem\\u003eNeophoca cinerea\\u003c/em\\u003e) [\\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e], loggerhead turtles (\\u003cem\\u003eCaretta caretta\\u003c/em\\u003e) [\\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e], and Aotearoa New Zealand takahē (\\u003cem\\u003ePorphyrio hochstetteri\\u003c/em\\u003e) [\\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e30\\u003c/span\\u003e]. The factors that sculpt microbial inhabitation of vertebrate hosts are likely many and complex but understanding them is critical to unravelling niche occupancy, plasticity and health in animals. Preliminary investigations have begun to discover how freshwater turtle microbiotas respond to environmental stressors [\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e], but further research is required in this field.\\u003c/p\\u003e \\u003cp\\u003eThe aims of this study were to expand our knowledge on microbiotas of freshwater chelonians and explore how location and differences in habitat quality can influence microbial assemblage in these species. To achieve this, the gut microbiotas of two species of turtle: eastern longneck turtle (\\u003cem\\u003eChelodina longicollis\\u003c/em\\u003e), and Macquarie River turtle (\\u003cem\\u003eEmydura macquarii\\u003c/em\\u003e), in multiple geographically distinct field sites across Victoria, Australia were investigated. Except for the pig-nosed turtle (\\u003cem\\u003eCarettochelys insculpta\\u003c/em\\u003e), all Australian freshwater turtles belong to the family \\u003cem\\u003eChelidae\\u003c/em\\u003e, and are characterised by being pleurodirus. Additionally, their forelimbs and hindlimbs are jointed and not paddle-shaped, they have distinct ankle-joints, and their feet are webbed with either four or five-claws [\\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e32\\u003c/span\\u003e]. The longneck turtle is a common species found throughout eastern Australia and occupies a broad range of freshwater habitats. They are opportunistic predators and are capable of long distance overland migrations [\\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e33\\u003c/span\\u003e]. The Macquarie River turtle is a short-necked species inhabiting larger rivers within the Murray-Darling River system and associated drainages west of the Great Dividing Range in south-eastern Australia, as well as coastal rivers in mid-eastern Australia [\\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e32\\u003c/span\\u003e]. They are opportunistically omnivorous, with the majority of their diet comprising filamentous algae and plant detritus, and the remainder consisting of vertebrate carrion and aquatic invertebrates [\\u003cspan citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e34\\u003c/span\\u003e]. Both species frequently inhabit the same waterbodies sympatrically, where their ranges overlap. The Macquarie River turtle is listed as threatened in Victoria due to continued population declines over the last three decades [\\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e35\\u003c/span\\u003e]. Our data explore how geography influences gut microbiotas in free-ranging freshwater turtles and will provide valuable insights into the chelonian-microbiota relationship thus aiding in directing future research endeavours.\\u003c/p\\u003e\"},{\"header\":\"Methods\",\"content\":\"\\u003cp\\u003eStudy populations\\u003c/p\\u003e \\u003cp\\u003eTurtles were trapped from multiple waterbodies in Victoria, Australia, in the Austral summer of 2022/23. Field sites included a mixture of waterbodies in both urban and rural areas, as well as ponds located within a sewerage treatment facility (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eRural waterbodies included Maloney\\u0026rsquo;s Wetland (MW, -36.102589, 146.872034) which is a naturally occurring creek system, and Barnawatha (BW, -36.0999377, 146.6240912) which was originally man-made as a waste-water treatment plant but was abandoned to rewilding nearly a decade ago. Urban waterbodies included Duck Pond (DP, -37.7732825, 145.0348189) and Ivanhoe Wetland (IW, -37.7734116, 145.0354874), within the Darebin Parklands, in Alphington, Melbourne. Melbourne is the second largest city in Australia with a population of approximately 4.9\\u0026nbsp;million people. DP is an old landfill site that became a permanent waterbody 40 years ago, and IW is a manmade wetland constructed during the early 1990s and is closely associated with the Darebin Creek system. DP and IW are separated by approximately 200m in a straight line. The sewerage treatment ponds were located within the Baranduda Wastewater Treatment Plant (BD, -36.1527907, 146.9600324) in Baranduda and are completely artificial.\\u003c/p\\u003e \\u003cp\\u003eSample collection\\u003c/p\\u003e \\u003cp\\u003eAt all sites, turtles were trapped using large, 6 hoop fyke nets with 28mm black, knotless mesh and a 2.5m wing with a 48cm drop and baited with chunks of lamb or chicken liver. Six to 10 nets were placed into each waterbody and left overnight. In the morning, traps were brought back to shore and turtles removed for sample collection. In Darebin Parklands (DP and IW), trapping only occurred for a single night at each site, and for all other locations traps were set for 2\\u0026ndash;3 nights. Once turtles had been removed from the nets, they were placed into dorsal recumbency, and a cotton swab was inserted into the cloaca and twirled so that it contacted the cloacal mucosa. The swab was then retracted, and the tip cut using flame-sterilised wire cutters and stored in 1ml of ZymoBIOMICS DNA/RNA Shield (Integrated Sciences) in a sterile Eppendorf tube. The Eppendorf tubes were then frozen and stored at -80\\u0026deg;C until DNA extraction could occur. All turtles were released alive at their point of capture following sample collection.\\u003c/p\\u003e \\u003cp\\u003eDNA extraction\\u003c/p\\u003e \\u003cp\\u003eDNA was extracted using the ZymoBIOMICS DNA Miniprep Kit (Integrated Sciences) according to the manufacturer\\u0026rsquo;s instructions. Following extraction, DNA was stored at -80\\u0026deg;C until amplicon sequencing could take place.\\u003c/p\\u003e \\u003cp\\u003e16S rRNA gene amplicon sequencing\\u003c/p\\u003e \\u003cp\\u003eThe V3-V4 region of 16S rRNA genes were PCR amplified with forward primer 5\\u0026rsquo; ACTCCTACGGGAGGCAGCAG 3\\u0026rsquo; and reverse primer 5\\u0026rsquo; GGACTACHVGGGTWTCTAAT 3\\u0026rsquo; using Q5 high fidelity polymerase (New England Biolabs) with a dual barcoding strategy [\\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e36\\u003c/span\\u003e]. The PCR cycling parameters were, 98\\u0026deg;C for 1 minute, 35 cycles of 98\\u0026deg;C for 10 seconds, 49\\u0026deg;C for 30 seconds, and 72\\u0026deg;C for 30 seconds, followed by a 10-minute extension at 72\\u0026deg;C. Sequencing was performed on an Illumina MiSeq system (2 x 300 bp).\\u003c/p\\u003e \\u003cp\\u003eData processing\\u003c/p\\u003e \\u003cp\\u003eSequence data was analysed using Quantitative Insights into Microbial Ecology 2 (QIIME2) version 220.6 [\\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e37\\u003c/span\\u003e], using the Divisive Amplicon Denoising Algorithm (DADA2) plugin for quality filtering, denoising, chimaera detection, and amplicon sequence variant (ASV) calling [\\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e]. ASVs were taxonomically classified using the SILVA database (v138.1) [\\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e]. An ASV abundance table with taxonomic assignments was produced for further analysis.\\u003c/p\\u003e \\u003cp\\u003eStatistical analyses\\u003c/p\\u003e \\u003cp\\u003eASV abundance data was analysed in R, utilising the package \\u0026lsquo;phyloseq\\u0026rsquo; [\\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e40\\u003c/span\\u003e]. Sequencing depth was explored using rarefaction curves and then data was rarefied to an even depth of 1500 reads. Alpha diversity was explored using Observed ASVs, Shannon index and Chao1 estimates. Alpha diversity was tested for normality using the Shapiro-Wilks test for each species. In longnecks, Observed (W\\u0026thinsp;=\\u0026thinsp;0.91, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.01), Chao1 (W\\u0026thinsp;=\\u0026thinsp;0.91, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.01), and Shannon (W\\u0026thinsp;=\\u0026thinsp;0.96, p\\u0026thinsp;=\\u0026thinsp;0.02), were all non-normally distributed and therefore comparisons were first made using the Kruskal-Wallis test, and then paired comparisons between groups were made using the pairwise Wilcoxon rank-sum test. For Macquarie River turtles Observed (W\\u0026thinsp;=\\u0026thinsp;0.91, p\\u0026thinsp;=\\u0026thinsp;0.15), Chao1 (W\\u0026thinsp;=\\u0026thinsp;0.91, p\\u0026thinsp;=\\u0026thinsp;0.15) and Shannon diversity (W\\u0026thinsp;=\\u0026thinsp;0.94, p\\u0026thinsp;=\\u0026thinsp;0.44) were all normally distributed and so comparisons were made between groups using a Welch two sample t-test. For both species beta diversity was investigated using Principal Co-ordinate Analysis (PCoA) on weighted UniFrac distances and Adonis tests to compare all locations within species, and then pairwise comparisons were made between all combinations of locations. Where variances between locations were found, we explored differentially abundant taxa using Linear discriminant analysis Effect Size (LEfSe) and LDA plots (cut-off value of 3) with the package \\u0026lsquo;microbiomeMarker\\u0026rsquo; [\\u003cspan citationid=\\\"CR41\\\" class=\\\"CitationRef\\\"\\u003e41\\u003c/span\\u003e]. The core microbiota was determined for each species by setting a prevalence threshold of 50% and a detection level of 0.05 and was represented using heat maps. For all pairwise tests, p-values were adjusted for multiple comparisons with Benjamini-Hochberg (BH) correction. For all statistical analyses significance was accepted if p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05.\\u003c/p\\u003e\"},{\"header\":\"Results\",\"content\":\"\\u003cp\\u003eIn total, 93 turtles were captured and sampled. At MW we captured 8 turtles comprised of a single species (Macquarie River turtle), at BW we captured 18 turtles of a single species (eastern longneck turtle), at BD we captured 27 turtles comprised of 2 species (eastern longneck turtle n\\u0026thinsp;=\\u0026thinsp;20, Macquarie River turtle n\\u0026thinsp;=\\u0026thinsp;7), and at DP and IW we captured 20 in each pond, of a single species (eastern longneck turtle). A total of 1,737,515 sequences were generated after quality checking and removal of chimaeras, giving an average of 18,683 sequences per sample. The taxonomic breakdown of sequence data yielded 29 bacterial phyla, 60 classes, 161 orders, 255 families, 415 genera, and 315 species.\\u003c/p\\u003e \\u003cp\\u003eEastern longneck turtle\\u003c/p\\u003e \\u003cp\\u003eThe five most predominate phyla were \\u003cem\\u003eProteobacteria\\u003c/em\\u003e (39%), \\u003cem\\u003eActinobacteriota\\u003c/em\\u003e (26.9%), \\u003cem\\u003eDeinococcota\\u003c/em\\u003e (8.57%), \\u003cem\\u003eBacteroidota\\u003c/em\\u003e (7.74%), and \\u003cem\\u003eFirmicutes\\u003c/em\\u003e (5.25%) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eA), and the five most abundant families were \\u003cem\\u003eComamonadaceae\\u003c/em\\u003e (18.1%), \\u003cem\\u003eIntrasporangiaceae\\u003c/em\\u003e (10.9%), \\u003cem\\u003eDeinococcaceae\\u003c/em\\u003e (9.5%), \\u003cem\\u003eRhodocyclaeceae\\u003c/em\\u003e (6.05%), and \\u003cem\\u003eLeptospiraceae\\u003c/em\\u003e (4.27%) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eB). Analysis of alpha diversity revealed that there were significant differences between localities for Observed ASVs (χ\\u0026sup2; = 19.35, df\\u0026thinsp;=\\u0026thinsp;3, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.01), Chao1 (χ\\u0026sup2; = 19.35, df\\u0026thinsp;=\\u0026thinsp;3, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.01), and Shannon diversity (χ\\u0026sup2; = 25.94, df\\u0026thinsp;=\\u0026thinsp;3, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.01) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eA). These observations were consistent when all samples were analysed in entirety, as well as for pairwise comparisons between certain combinations of locations (Additional file 1). For beta diversity we detected differences between locations when samples were analysed together (df\\u0026thinsp;=\\u0026thinsp;3, SS\\u003csub\\u003eT\\u003c/sub\\u003e = 4.56, R\\u003csup\\u003e2\\u003c/sup\\u003e\\u0026thinsp;=\\u0026thinsp;0.34, f.model\\u0026thinsp;=\\u0026thinsp;12.63, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.01) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003eA). Differences existed between all combinations of locations when pairwise comparisons, with BH correction of p-values, were done (Additional file 1). LefSe analysis between locations revealed 91 significant biomarkers between groups with 19 of these found in animals from IW, 24 from DP, 23 from BW, and 25 from BD (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003eA). For core microbiota 49 ASVs met the selection criteria (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003eA).\\u003c/p\\u003e \\u003cp\\u003eMacquarie River turtle\\u003c/p\\u003e \\u003cp\\u003eThe five most predominate phyla were \\u003cem\\u003eProteobacteria\\u003c/em\\u003e (32.1%), \\u003cem\\u003eDeinococcota\\u003c/em\\u003e (24.5%), \\u003cem\\u003eBacteroidota\\u003c/em\\u003e (21.2%), \\u003cem\\u003eActinobacteriota\\u003c/em\\u003e (12.8%), and \\u003cem\\u003eCyanobacteria\\u003c/em\\u003e (6.12%) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003ec), and the five most abundant families were \\u003cem\\u003eDeinococcaceae\\u003c/em\\u003e (26.2%), \\u003cem\\u003eComamonadaceae\\u003c/em\\u003e (23.8%), \\u003cem\\u003eWeeksellaceae\\u003c/em\\u003e (17.3%), \\u003cem\\u003eNostocaceae\\u003c/em\\u003e (3.94%), and \\u003cem\\u003eFlavobacteriaceae\\u003c/em\\u003e (2.16%) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003ed). Analysis of alpha diversity revealed that there were no significant differences between localities for Observed ASVs (t=-0.02, df\\u0026thinsp;=\\u0026thinsp;11.83, p\\u0026thinsp;=\\u0026thinsp;0.98), Chao1 (t=-0.02, df\\u0026thinsp;=\\u0026thinsp;11.83, p\\u0026thinsp;=\\u0026thinsp;0.98), and Shannon diversity (t=-0.29, df\\u0026thinsp;=\\u0026thinsp;9.11, p\\u0026thinsp;=\\u0026thinsp;0.78) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eb). Conversely, for beta diversity we detected a significant difference between locations (df\\u0026thinsp;=\\u0026thinsp;1, SS\\u003csub\\u003eT\\u003c/sub\\u003e = 0.35, R\\u003csup\\u003e2\\u003c/sup\\u003e\\u0026thinsp;=\\u0026thinsp;0.14, f.model\\u0026thinsp;=\\u0026thinsp;2.16, p\\u0026thinsp;=\\u0026thinsp;0.03) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003eb). LefSe analysis between locations revealed 40 significant biomarkers between groups with 13 of these found in MW, and 27 found in BD (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003eb). For core microbiotae 36 ASVs met the selection criteria (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003eB).\\u003c/p\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003eIn this study the gut microbiota composition in two species of Australian freshwater chelonians, the eastern longneck turtle and the Macquarie River turtle, are described. We found that in both species the predominant phylum was \\u003cem\\u003eProteobacteria\\u003c/em\\u003e, followed by \\u003cem\\u003eActinobacteriota\\u003c/em\\u003e, \\u003cem\\u003eDeinococcota\\u003c/em\\u003e, \\u003cem\\u003eBacteroidota\\u003c/em\\u003e, and \\u003cem\\u003eFirmicutes\\u003c/em\\u003e in the eastern longneck, and \\u003cem\\u003eDeinococcota\\u003c/em\\u003e, \\u003cem\\u003eBacteroidota\\u003c/em\\u003e, \\u003cem\\u003eActinobacteriota\\u003c/em\\u003e, and \\u003cem\\u003eCyanobacteria\\u003c/em\\u003e in Macquarie River turtles. There is considerable variability of gut microbiota composition in chelonians, with \\u003cem\\u003eProteobacteria\\u003c/em\\u003e dominating in other species such as map turtles (\\u003cem\\u003eGraptemys pseudogeographica\\u003c/em\\u003e) [\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e], wild Beal\\u0026rsquo;s eyed turtles (\\u003cem\\u003eSacalia bealei\\u003c/em\\u003e) [\\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e], and also in all species of female sea turtles that were sampled during nesting [\\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e42\\u003c/span\\u003e]. However, \\u003cem\\u003eFirmicutes\\u003c/em\\u003e has been reported as the most prevalent phylum in other chelonians including Seychelles giant tortoises (\\u003cem\\u003eAldabrachelys gigantea\\u003c/em\\u003e) [\\u003cspan citationid=\\\"CR43\\\" class=\\\"CitationRef\\\"\\u003e43\\u003c/span\\u003e], southern river terrapins (\\u003cem\\u003eBatagur affinis\\u003c/em\\u003e) [\\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e], captive Beal\\u0026rsquo;s eyed turtles [\\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e], painted turtles (\\u003cem\\u003eChrysems picta\\u003c/em\\u003e) [\\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e], one population of flatback turtles (\\u003cem\\u003eNatator depressus\\u003c/em\\u003e) [\\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e], and a range of sea turtles under different age, sex and health classes [\\u003cspan citationid=\\\"CR44\\\" class=\\\"CitationRef\\\"\\u003e44\\u003c/span\\u003e]. Interestingly, a predominance of \\u003cem\\u003eFirmicutes\\u003c/em\\u003e was also seen in Macquarie River turtles captured from undisclosed waterways in Queensland, Australia [\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e]. Making meaningful comparisons between studies to explain observed variance is difficult as microbiota investigations are complicated by differences in methodology [\\u003cspan citationid=\\\"CR45\\\" class=\\\"CitationRef\\\"\\u003e45\\u003c/span\\u003e], phylogenetic history of species sampled [\\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e42\\u003c/span\\u003e], physiological state of hosts [\\u003cspan citationid=\\\"CR46\\\" class=\\\"CitationRef\\\"\\u003e46\\u003c/span\\u003e], and local environmental factors [\\u003cspan citationid=\\\"CR47\\\" class=\\\"CitationRef\\\"\\u003e47\\u003c/span\\u003e]. Therefore, until protocols to standardise field and laboratory practices have been agreed upon, caution should be taken when inferring which factors have physiological effects on microbiota based on differences between studies.\\u003c/p\\u003e \\u003cp\\u003eThis investigation into the gut microbiota in freshwater chelonians has shown that bacterial communities differ significantly among turtles of the same species but originating from geographically distinct populations. These differences were apparent in both composition and diversity and highlight the importance of interpreting microbiota data in the context of locality. Geography has been shown to play a key role in driving gut microbial ecology in vertebrate hosts and is likely to be related to deterministic processes such as food availability, inter/intraspecific competition, host dispersal and local environmental factors [\\u003cspan additionalcitationids=\\\"CR49 CR50\\\" citationid=\\\"CR48\\\" class=\\\"CitationRef\\\"\\u003e48\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR51\\\" class=\\\"CitationRef\\\"\\u003e51\\u003c/span\\u003e]. However, these findings are not consistent across all vertebrate classes with location not an important factor in determining microbiota composition in eastern garter snakes (\\u003cem\\u003eThamnophis sirtalis sirtalis\\u003c/em\\u003e) and northern watersnakes (\\u003cem\\u003eNeridia sipedon sipedon\\u003c/em\\u003e) [\\u003cspan citationid=\\\"CR52\\\" class=\\\"CitationRef\\\"\\u003e52\\u003c/span\\u003e]. Correctly identifying the processes responsible for observed disparities between populations of wild animals is difficult because how microorganisms colonise the gut of vertebrates is multifaceted and dependent on a suite of host, microbe, and spatial ecology features.\\u003c/p\\u003e \\u003cp\\u003eDifferences in alpha diversity metrics existed for all populations of eastern longneck turtles. A consistent finding was that animals from urban ponds in the middle of Melbourne (DP and IW) scored lowest for all alpha diversity measures in comparison to the other study locations (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eA). These observations were particularly apparent in animals captured from DP, in which Observed ASVs, Chao1 and Shannon diversity were all much lower than the other localities. Both DP and IW are in areas of high public visitation and there may be significant public interaction with the animals at these sites. Interestingly, animals captured from the wastewater treatment plant at BD had higher alpha diversity metrics than both DP and IW. The ponds at BD are all manmade and constructed of concrete, there is no vegetation surrounding or within the ponds, and given that it is a facility used for processing human waste it would be easy to assume that this was the most disturbed habitat that we captured turtles. Human interaction with turtles is lower at BD than at DP and IW and only occurs when maintenance of the treatment ponds is necessary. Turtles from BW had the highest alpha diversity scores, and this was the least disturbed habitat with almost no human visitation. For longneck turtles it appears that presence of humans may be a more significant factor in reducing microbiota richness and diversity than habitat quality. Anthropogenic pressures have been shown to considerably alter gut microbiota of a range of wildlife including Tome\\u0026rsquo;s spiny rats (\\u003cem\\u003eProechimys semispinosus\\u003c/em\\u003e) [\\u003cspan citationid=\\\"CR53\\\" class=\\\"CitationRef\\\"\\u003e53\\u003c/span\\u003e], swan geese (\\u003cem\\u003eAnser cygnoides\\u003c/em\\u003e) [\\u003cspan citationid=\\\"CR54\\\" class=\\\"CitationRef\\\"\\u003e54\\u003c/span\\u003e], Kuhl\\u0026rsquo;s pipistrelle bats (\\u003cem\\u003ePipistrellus kuhlii\\u003c/em\\u003e) [\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e], and olive baboons (\\u003cem\\u003ePapio anubis\\u003c/em\\u003e) [\\u003cspan citationid=\\\"CR55\\\" class=\\\"CitationRef\\\"\\u003e55\\u003c/span\\u003e], and there are concerns that these disturbances in microbial ecology may have negative implications for vertebrate conservation [\\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e22\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR56\\\" class=\\\"CitationRef\\\"\\u003e56\\u003c/span\\u003e]. In contrast to eastern longneck turtles, no significant differences in alpha diversity due to location were found for Macquarie River turtles and it is possible that specific physiological traits, such as omnivory, in this species ensures a more stable environment for gut microbiotas.\\u003c/p\\u003e \\u003cp\\u003eThe role that diet may be playing in driving differences in bacterial composition in our samples is unknown. Eastern longneck turtles are obligate carnivores that appear to have limited dietary preferences and will feed on almost any vertebrate or invertebrate that they can apprehend and subdue [\\u003cspan citationid=\\\"CR57\\\" class=\\\"CitationRef\\\"\\u003e57\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR58\\\" class=\\\"CitationRef\\\"\\u003e58\\u003c/span\\u003e]. In contrast, the Macquarie River turtle is omnivorous with much of their diet consisting of filamentous algae supplemented with carrion when available [\\u003cspan citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e34\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR59\\\" class=\\\"CitationRef\\\"\\u003e59\\u003c/span\\u003e]. Given the relative dietary plasticity seen in both of these species, geographic variation in food consumption likely results from local differences in prey abundance and this may be a significant factor in shaping gut microbiota composition. Other influences on dietary intake in Australian freshwater turtles are competition with fish [\\u003cspan citationid=\\\"CR57\\\" class=\\\"CitationRef\\\"\\u003e57\\u003c/span\\u003e], and inter-species antagonism with other chelonians [\\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e35\\u003c/span\\u003e]. In this investigation we made no attempt to assess food availability or heterospecific behaviour and therefore their roles in resource partitioning and as a determinant of microbial community composition remains unknown. One further potentially significant confounder on gut microbiotas is \\u0026ldquo;Good Samaritan\\u0026rdquo; feeding of turtles in public places. While this practice was not directly observed during trapping events, feeding of wildlife is common in Melbourne [\\u003cspan citationid=\\\"CR60\\\" class=\\\"CitationRef\\\"\\u003e60\\u003c/span\\u003e], and access to anthropogenic food sources has been shown to negatively impact the gut microbiotas of multiple vertebrate species [\\u003cspan citationid=\\\"CR55\\\" class=\\\"CitationRef\\\"\\u003e55\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR61\\\" class=\\\"CitationRef\\\"\\u003e61\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR62\\\" class=\\\"CitationRef\\\"\\u003e62\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eAn interesting finding in this investigation was the significant differences in both alpha and beta diversity between longneck turtles originating from ponds in the Darebin Parklands. These ponds are separated by approximately 200m in a straight line which should not be a significant obstacle for this species to overcome. Eastern longneck turtles are capable of long terrestrial migrations to escape unfavourable conditions [\\u003cspan citationid=\\\"CR63\\\" class=\\\"CitationRef\\\"\\u003e63\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR64\\\" class=\\\"CitationRef\\\"\\u003e64\\u003c/span\\u003e], made possible by their resistance to desiccation [\\u003cspan citationid=\\\"CR65\\\" class=\\\"CitationRef\\\"\\u003e65\\u003c/span\\u003e]. The results of this study may indicate that there is little seasonal fluctuation in resources available to turtles within these ponds negating the need for individuals to emigrate between waterbodies. In the event that turtles do translocate to new ponds, if and how long gut microbiotas take to assimilate to their new environments remains unknown.\\u003c/p\\u003e \\u003cp\\u003eFor both species sampled, the bacterial family \\u003cem\\u003eComamonadaceae\\u003c/em\\u003e was routinely identified in almost all samples. These bacteria form a major group of the \\u003cem\\u003eBeta-Proteobacteria\\u003c/em\\u003e and are characterised as being poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV)-degrading denitrifying bacteria frequently isolated from sewerage sludge [\\u003cspan citationid=\\\"CR66\\\" class=\\\"CitationRef\\\"\\u003e66\\u003c/span\\u003e]. This result is not surprising given that many of our turtles originated from either active, or decommissioned sewerage and wastewater treatment plants. What is unclear is if these bacteria form a normal component of the gut microflora in these turtles, or if they are simply environmental species that have been inadvertently sequenced. However, we did identify this family in animals originating from MW, which is a natural waterbody with no history of use as a wastewater treatment facility, and they have also been identified as normal flora in a range of vertebrates including fish, birds and humans [\\u003cspan additionalcitationids=\\\"CR68\\\" citationid=\\\"CR67\\\" class=\\\"CitationRef\\\"\\u003e67\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR69\\\" class=\\\"CitationRef\\\"\\u003e69\\u003c/span\\u003e]. Further exploration of turtles from more pristine waterways is warranted to determine the prevalence of this bacterial family in chelonians, and its significance to turtle physiology.\\u003c/p\\u003e\"},{\"header\":\"Conclusions\",\"content\":\"\\u003cp\\u003eThe analysis of the bacterial microbiota of wild freshwater chelonians indicated that microbial communities differ significantly among individuals of the same species that originate from different populations. This finding highlights the importance of interpreting microbiota data in the context of environment, as it appears that local effects significantly alter microbial composition in chelonians. Of particular interest was the differences observed between turtles from DP and IW given their proximity. Eastern longneck turtles are known to undergo long terrestrial sojourns and thus it is possible that there is movement of individuals between these ponds. If this does occur, then it suggests gut microbiotas assimilate to local conditions but how long this takes is unknown at this stage, and future research should be aimed at determining plasticity of gut microbiotas in individual turtles.\\u003c/p\\u003e\"},{\"header\":\"Abbreviations\",\"content\":\"\\u003cdiv class=\\\"DefinitionList\\\"\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eASV\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eAmplicon sequence variant\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eBD\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eBaranduda\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eBW\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eBarnawatha\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eDNA\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eDeoxyribonucleic acid\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eDP\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eDuck Pond\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eIW\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eIvanhoe Wetland\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eMW\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eMaloney\\u0026rsquo;s Wetland\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eNCBI\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eNational Centre for Biotechnology Information\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003ePCoA\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003ePrincipal coordinate analysis\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003erRNA\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eRibosomal ribonucleic acid.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003c/div\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003eEthics approval\\u003c/p\\u003e\\n\\u003cp\\u003eThis study was approved by The University of Melbourne Office of Research Ethics and Integrity (Ethics ID: 2022-24808-32226-4) and all experiments were performed in accordance with relevant guidelines and regulations. Turtles were trapped and sampled under permit 10010480 from the Department of Environment, Land, Water and Planning, and permit number RP1497 from the Victorian Fisheries Authority. All turtles were released alive at their point of capture immediately after sampling had been completed.\\u003c/p\\u003e\\n\\u003cp\\u003eCompeting interests\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors declare that they have no competing interests.\\u003c/p\\u003e\\n\\u003cp\\u003eFunding\\u003c/p\\u003e\\n\\u003cp\\u003eTFS is supported by a McKenzie Postdoctoral Fellowship at the University of Melbourne.\\u003c/p\\u003e\\n\\u003cp\\u003eAuthors\\u0026rsquo; contributions\\u003c/p\\u003e\\n\\u003cp\\u003eTFS was responsible for experimental design, collecting samples and analysing and interpreting data. RJM and TTHV were responsible for16S rRNA gene amplicon production and sequencing, bioinformatics, and data interpretation. All authors were major contributors in writing the manuscript and have approved the final document.\\u003c/p\\u003e\\n\\u003cp\\u003eAvailability of data and materials\\u003c/p\\u003e\\n\\u003cp\\u003eAll data presented here and in the supplementary material have been submitted to The National Center for Biotechnology Information (www.ncbi.nlm.nih.gov) and can be accessed under accession number xxx\\u003c/p\\u003e\\n\\u003cp\\u003eAcknowledgments\\u003c/p\\u003e\\n\\u003cp\\u003eWe thank James Van Dyke, Donald McKnight, Angela Simms, Tilli Beaumont, Emma Kynaston, Peter Wiltshire, Kim Davis, Dan Guinto and Jasper White for assistance in placing traps and processing turtles.\\u0026nbsp;\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n\\u003cli\\u003ePeixoto RS, Harkins DM, Nelson KE. 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Numerical ecology validates a biogeographical distribution and gender-based effect on mucosa-associated bacteria along the human colon\\u003cstrong\\u003e.\\u003c/strong\\u003e ISME J\\u003cem\\u003e \\u003c/em\\u003e2011, 5\\u003cstrong\\u003e:\\u003c/strong\\u003e801-809.\\u003c/li\\u003e\\n\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":true,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":false,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true},\"keywords\":\"Chelonian, eastern longneck turtle, freshwater turtle, location, Macquarie River turtle, microbiota\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-4445807/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-4445807/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003ch2\\u003eBackground\\u003c/h2\\u003e \\u003cp\\u003eThe gut microbiota of vertebrates is malleable and may be shaped by both intrinsic and extrinsic factors. Here, the effect that geography has on the gut microbiota of two species of Australian freshwater chelonians, eastern longneck turtle (\\u003cem\\u003eChelodina longicollis\\u003c/em\\u003e) and Macquarie River turtle (\\u003cem\\u003eEmydura macquarii\\u003c/em\\u003e), captured from waterbodies with different levels of anthropogenic pressure was investigated. We analysed the microbiota composition, structure and diversity through 16S rRNA gene amplicon sequencing. It was hypothesized that animals from less disturbed environments would harbour a more diverse gut microbial population.\\u003c/p\\u003e\\u003ch2\\u003eResults\\u003c/h2\\u003e \\u003cp\\u003eThe gut microbiotas from 93 turtles (\\u003cem\\u003eC. longicollis\\u003c/em\\u003e n\\u0026thinsp;=\\u0026thinsp;78; \\u003cem\\u003eE. macquarii\\u003c/em\\u003e n\\u0026thinsp;=\\u0026thinsp;15), from five locations, were analysed. For both species the most predominant phylum was \\u003cem\\u003eProteobacteria\\u003c/em\\u003e. Gut microbiota alpha diversity varied significantly between the \\u003cem\\u003eC. longicollis\\u003c/em\\u003e from all locations, but no differences were found for \\u003cem\\u003eE. macquarii\\u003c/em\\u003e. In \\u003cem\\u003eC. longicollis\\u003c/em\\u003e, turtles from wetlands within the centre of Melbourne had the lowest alpha diversity metrics, while the highest alpha diversity values were seen in turtles captured from an undisturbed rural waterbody. Beta diversity, obtained by weighted UniFrac distance, showed significant differences between location of capture for both species of turtles in this investigation. For \\u003cem\\u003eC. longicollis\\u003c/em\\u003e, 91 biomarkers were identified responsible for explaining differences between locations, and in \\u003cem\\u003eE. macquarii\\u003c/em\\u003e 40 biomarkers were found. Core community analysis revealed 49 and 36 ASVs shared between populations of \\u003cem\\u003eC. longicollis\\u003c/em\\u003e and \\u003cem\\u003eE. macquarii\\u003c/em\\u003e respectively.\\u003c/p\\u003e\\u003ch2\\u003eConclusions\\u003c/h2\\u003e \\u003cp\\u003eThe study showed that gut microbiota composition of freshwater turtles was significantly influenced by locality and that the disrupted environments may reduce microbial diversity in \\u003cem\\u003eC. longicollis\\u003c/em\\u003e. The results highlight the need to interpret chelonian microbiota data in the context of geography and human disturbance of the environment.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Location matters: variations in gut microbiota composition of spatially separated freshwater turtles\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2024-05-31 13:49:47\",\"doi\":\"10.21203/rs.3.rs-4445807/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"7ca49080-9685-4dc7-967f-d96b4b9d2d27\",\"owner\":[],\"postedDate\":\"May 31st, 2024\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"posted\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2024-07-26T01:02:21+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2024-05-31 13:49:47\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-4445807\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-4445807\",\"identity\":\"rs-4445807\",\"version\":[\"v1\"]},\"buildId\":\"qtupq5eGEP_6zYnWcrvyt\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}