[en] The microbiome is an important consideration for the conservation of endangered species. Studies provided evidence of the effect of behavior and habitat change on the microbiota of wild animals and reported various inferences. It indicates the complexity of factors influencing microbiota diversity, including incomplete sampling procedures. Data abnormality may arise due to the procedures warranting preliminary analysis, such as rarefaction, before downstream analysis. This present study demonstrated the effect of data rarefaction and aggregation on the comparison of wild rusa deer's gut microbial diversity. Eighty-five feces samples were collected from 11 deer populations inhabiting three national parks in Java and Bali islands. Using the Illumina Nova-Seq platform, fragments of 16s rRNA gene were sequenced, and raw data of 51,389 reads corresponding to 2 domains, 22 phyla, 45 classes, 83 orders, 182 families, and 460 genera of bacteria were obtained. Data rarefaction was applied at two different library sizes (minimum and fixed) and aggregation (11 populations into 3 research sites) to investigate its effect on the microbial diversity comparison. There are significant differences in alpha diversity between populations, but not research sites, at all library sizes of rarefaction. A similar finding is also found in beta diversity. Moreover, data rarefaction and aggregation result in different values of the diversity metrics. This present study shows that statistical analysis remains a substantial concern in microbiome studies applied to conservation biology. It suggests reporting a more detailed data normalization in microbiome studies as an inherent control of suboptimal sampling, particularly when involving feces.
Disciplines :
Zoology
Author, co-author :
Subrata, Sena A ; Faculty of Forestry, Universitas Gadjah Mada, Yogyakarta, Indonesia. adisubrata@ugm.ac.id
Yuda, Pramana ; Faculty of Technobiology, Universitas Atma Jaya Yogyakarta, Yogyakarta, Indonesia
Artama, Wayan T ; Faculty of Veterinary Medicine, Universitas Gadjah Mada, Yogyakarta, Indonesia
de-Garine Wichatitsky, Michel ; Faculty of Veterinary Medicine, Kasetsart University, Bangkok, Thailand
André, Adrien ; Conservation Genetics Unit, Department of Life Sciences, University of Liège, Liege, Belgium
Michaux, Johan ; Université de Liège - ULiège > Integrative Biological Sciences (InBioS)
Language :
English
Title :
Rusa deer microbiota: the importance of preliminary data analysis for meaningful diversity comparisons.
Publication date :
January 2025
Journal title :
International Microbiology
ISSN :
1139-6709
eISSN :
1618-1905
Publisher :
Springer Science and Business Media Deutschland GmbH, Switzerland
The authors are grateful to the Directorate General of Higher Education, Research, and Technology\u2013the Ministry of Education, Culture, Research, and Technology of the Republic of Indonesia for funding this research. The authors also thank the French Ministry of Foreign Affairs and International Development (MAEDI) and the French Ministry of Higher Education and Research (MESR) for supporting this research collaboration. The authors also acknowledge the Directorate General of Nature and Ecosystem Conservation\u2013Ministry of Environment and Forestry of the Republic of Indonesia for issuing a sample collection permit.Authors SAS, PY, and WTA received funding from the Directorate General of Higher Education, Research, and Technology, Indonesia, and authors MdGW, AA, and JM had support from the French Ministry of Foreign Affairs and International Development and the French Ministry of Higher Education and Research.
J. Aitchison The statistical analysis of compositional data J R Statist Soc B 1982 44 2 139 177 10.1111/j.2517-6161.1982.tb01195.x
A. Alberdi G. Martin Bideguren O. Aizpurua Diversity and compositional changes in the gut microbiota of wild and captive vertebrates: a meta-analysis Sci Rep 2021 11 22660 1:CAS:528:DC%2BB3MXisFClsLjN 10.1038/s41598-021-02015-6 34811423 8608908
K.R. Amato C.J. Yeoman A. Kent N. Righini F. Carbonero A. Estrada H. Rex Gaskins R.M. Stumpf S. Yildirim M. Torralba M. Gillis B.A. Wilson K.E. Nelson B.A. White S.R. Leigh Habitat degradation impacts black howler monkey (Alouatta pigra) gastrointestinal microbiomes ISME J 2013 7 1344 1353 1:CAS:528:DC%2BC3sXhtValt73P 10.1038/ismej.2013.16 23486247 3695285
A. André A. Mouton V. Millien J. Michaux Liver microbiome of Peromyscus leucopus, a key reservoir host species for emerging infectious diseases in North America Infect Genet Evol 2017 52 10 18 10.1016/j.meegid.2017.04.011 28412525
S. Bahrndorff T. Alemu T. Alemneh J. Lund Nielsen The microbiome of animals: implications for conservation biology Int J Genomics 2016 2016 1 7 1:CAS:528:DC%2BC28XhslaktrbE 10.1155/2016/5304028
C. Barelli D. Albanese C. Donati M. Pindo C. Dallago F. Rovero D. Cavalieri T.K. Michael H.H. Christine C. De Filippo Habitat fragmentation is associated to gut microbiota diversity of an endangered primate: implications for conservation Sci Rep 2015 5 14862 1:CAS:528:DC%2BC2MXhs1WlsLjK 10.1038/srep14862 26445280 4595646
A. Borbón-García A. Reyes M. Vives-Flórez S. Caballero Captivity shapes the gut microbiota of Andean bears: insights into health surveillance Front Microbiol 2017 8 1316 10.3389/fmicb.2017.01316 28751883 5507997
C. Cando-Dumancela C. Liddicoat D. McLeod J.M. Young M.F. Breed A guide to minimize contamination issues in microbiome restoration studies Restor Ecol 2021 29 e13358 10.1111/rec.13358
J. Chong P. Liu G. Zhou J. Xia Using MicrobiomeAnalyst for comprehensive statistical, functional, and meta-analysis of microbiome data Nat Protoc 2020 15 799 821 1:CAS:528:DC%2BB3cXislegsr8%3D 10.1038/s41596-019-0264-1 31942082
T.M. DeJong A comparison of three diversity indices based on their components of richness and evenness. Source Oikos 1975 26 222 227 10.2307/3543712
Edgar R (2010) Usearch. https://www.osti.gov/servlets/purl/1137186.
K.M. Gibson B.N. Nguyen L.M. Neumann M. Miller P. Buss S. Daniels M.J. Ahn K.A. Crandall B. Pukazhenthi Gut microbiome differences between wild and captive black rhinoceros – implications for rhino health Sci Rep 2019 9 7570 1:CAS:528:DC%2BC1MXhtVGhu7nK 10.1038/s41598-019-43875-3 31138833 6538756
B. Goossens M. Salgado-lynn Advances and difficulties of molecular tools for carnivore conservation in the tropics Raffles Bull Zool 2013 28 43 53
W. Guo S. Mishra C. Wang H. Zhang R. Ning F. Kong B. Zeng J. Zhao Y. Li Comparative study of gut microbiota in wild and captive giant pandas (Ailuropoda melanoleuca) Genes 2019 10 10 827 1:CAS:528:DC%2BC1MXitlSis7nF 10.3390/genes10100827 31635158 6826394
J. Hong U. Karaoz P. De Valpine W. Fithian To rarefy or not to rarefy: robustness and efficiency trade-offs of rarefying microbiome data Bioinformatics 2022 38 2389 2396 1:CAS:528:DC%2BB38XhtlynsrfK 10.1093/bioinformatics/btac127 35212706
J.B. Hughes J.J. Hellmann The application of rarefaction techniques to molecular inventories of microbial diversity Methods Enzymol 2005 397 292 308 1:CAS:528:DC%2BD2sXlvFymu70%3D 10.1016/S0076-6879(05)97017-1 16260298
M.H. Iman P.C. Kuswandi S.A. Subrata Genetic variation of the native Rusa deer (Rusa timorensis) in Java and Bali (Indonesia) as revealed using non-invasive sampling Biodiversitas 2024 25 1 355 360 10.13057/biodiv/d250241
A. Klindworth E. Pruesse T. Schweer J. Peplies C. Quast M. Horn F.O. Glöckner Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies Nucleic Acids Res 2013 41 1 e1 e1 1:CAS:528:DC%2BC3sXhsFagtQ%3D%3D 10.1093/nar/gks808 22933715
H. Lin P.S. Das Analysis of microbial compositions: a review of normalization and differential abundance analysis NPJ Biofilms Microbiomes 2020 6 1 60 10.1038/s41522-020-00160-w 33268781 7710733
T. Liu H. Zhao T. Wang An empirical Bayes approach to normalization and differential abundance testing for microbiome data BMC Bioinformatics 2020 21 225 10.1186/s12859-020-03552-z 32493208 7268703
F. Mahé L. Czech A. Stamatakis C. Quince C. de Vargas M. Dunthorn T. Rognes Swarm v3: towards tera-scale amplicon clustering Bioinformatics 2021 38 1 267 269 1:CAS:528:DC%2BB38Xhsl2ksb4%3D 10.1093/bioinformatics/btab493 34244702 8696092
D.T. McKnight R. Huerlimann D.S. Bower L. Schwarzkopf R.A. Alford K.R. Zenger Methods for normalizing microbiome data: an ecological perspective Methods Ecol Evol 2019 10 389 400 10.1111/2041-210X.13115
M.H. Murray E.W. Lankau A.D. Kidd C.N. Welch T. Ellison H.C. Adams E.K. Lipp S.M. Hernandez Gut microbiome shifts with urbanization and potentially facilitates a zoonotic pathogen in a wading bird PLoS One 2020 15 3 e0220926 1:CAS:528:DC%2BB3cXlvFSntr4%3D 10.1371/journal.pone.0220926 32134945 7058277
A.Y. Pan Statistical analysis of microbiome data: the challenge of sparsity Curr Opin Endocr Metab Res 2021 19 35 40 1:CAS:528:DC%2BB3MXit1eltrvM 10.1016/j.coemr.2021.05.005
J.N. Paulson O. Colin Stine H.C. Bravo M. Pop Differential abundance analysis for microbial marker-gene surveys Nat Methods 2013 10 1200 1202 1:CAS:528:DC%2BC3sXhsFaksbvP 10.1038/nmeth.2658 24076764 4010126
V.R. Prabhu V.R. Wasimuddin R. Kamalakkannan M.S. Arjun M. Nagarajan Consequences of domestication on gut microbiome: a comparative study between wild Gaur and domestic Mithun Front Microbiol 2020 11 133 10.3389/fmicb.2020.00133 32158434 7051944
C.H. Sun H.Y. Liu B. Liu B.D. Yuan C.H. Lu Analysis of the gut microbiome of wild and captive Père David’s deer Front Microbiol 2019 10 2331 10.3389/fmicb.2019.02331 31636626 6787558
Y. Sun Y. Sun Z. Shi Z. Liu C. Zhao T. Lu H. Gao F. Zhu R. Chen J. Zhang R. Pan B. Li L. Teng S. Guo Gut microbiota of wild and captive Alpine musk deer (Moschus chrysogaster) Front Microbiol 2020 10 3156 10.3389/fmicb.2019.03156 32038587 6985557
Sutomo E. van Etten Savanna plant communities in the wetter parts of the Indonesian archipelago Folia Geobot 2021 56 193 204 10.1007/s12224-021-09401-y
L. Tang Y. Li A. Srivathsan Y. Gao K. Li D. Hu D. Zhang Gut microbiomes of endangered Przewalski’s horse populations in short- and long-term captivity: implication for species reintroduction based on the soft-release strategy Front Microbiol 2020 11 363 10.3389/fmicb.2020.00363 32226419 7081077
B.K. Trevelline S.S. Fontaine B.K. Hartup K.D. Kohl Conservation biology needs a microbial renaissance: a call for the consideration of host-associated microbiota in wildlife management practices Proc R Soc B 2019 286 1895 20182448 10.1098/rspb.2018.2448 30963956 6364583
M.C.B. Tsilimigras A.A. Fodor Compositional data analysis of the microbiome: fundamentals, tools, and challenges Ann Epidemiol 2016 26 330 335 10.1016/j.annepidem.2016.03.002 27255738
Q. Wang G.M. Garrity J.M. Tiedje J.R. Cole Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy Appl Environ Microbiol 2007 73 16 5261 5267 1:CAS:528:DC%2BD2sXpsleqtrc%3D 10.1128/AEM.00062-07 17586664 1950982
F. Wei Q. Wu Y. Hu G. Huang Y. Nie L. Yan Conservation metagenomics: a new branch of conservation biology Sci China Life Sci 2019 62 168 178 1:CAS:528:DC%2BC1cXis1Snt7zN 10.1007/s11427-018-9423-3 30588567
S. Weiss Z.Z. Xu S. Peddada A. Amir K. Bittinger A. Gonzalez C. Lozupone J.R. Zaneveld Y. Vázquez-Baeza A. Birmingham E.R. Hyde R. Knight Normalization and microbial differential abundance strategies depend upon data characteristics Microbiome 2017 5 1 18 10.1186/s40168-017-0237-y
A.G. West D.W. Waite P. Deines D.G. Bourne A. Digby V.J. McKenzie M.W. Taylor The microbiome in threatened species conservation Biol Conserv 2019 229 85 98 10.1016/j.biocon.2018.11.016
T. Whitten R.E. Soeriaatmaja S.A. Afiff The ecology of Java and Bali 1996 Hong Kong Periplus Edition
A.D. Willis Rarefaction, alpha diversity, and statistics Front Microbiol 2019 10 2407 10.3389/fmicb.2019.02407 31708888 6819366
Y. Xia J. Sun D.-G. Chen Statistical analysis of microbiome data with R 2018 Singapore Springer Singapore 10.1007/978-981-13-1534-3
H. Yang X. Leng H. Du J. Luo J. Wu Q. Wei Adjusting the prerelease gut microbial community by diet training to improve the postrelease fitness of captive-bred Acipenser dabryanus Front Microbiol 2020 11 488 10.3389/fmicb.2020.00488 32373077 7186344
M.A. Zemanova Poor implementation of non-invasive sampling in wildlife genetics studies Rethinking Ecol 2019 4 119 132 10.3897/rethinkingecology.4.32751
L. Zhu J. Wang S. Bahrndorff Editorial: The wildlife gut microbiome and its implication for conservation biology Front Microbiol 2021 12 10 13 10.3389/fmicb.2021.697499