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Research Article | Open Access

A network meta-analysis on comparison of invasive and non-invasive sampling methods to characterize intestinal microbiota of birds

Tianlong Zhoua, Kasun H. Bodawattab, Aiwu Jianga( )
Guangxi Key Laboratory of Forest Ecology and Conservation, College of Forestry, Guangxi University, Nanning, 530004, China
Natural History Museum of Denmark, University of Copenhagen, Copenhagen, Denmark
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Abstract

Birds maintain complex and intimate associations with a diverse community of microbes in their intestine. Multiple invasive and non-invasive sampling methods are used to characterize these communities to answer a multitude of eco-evolutionary questions related to host-gut microbiome symbioses. However, the comparability of these invasive and non-invasive sampling methods is sparse with contradicting findings. Through performing a network meta-analysis for 13 published bird gut microbiome studies, here we attempt to investigate the comparability of these invasive and non-invasive sampling methods. The two most used non-invasive sampling methods (cloacal swabs and fecal samples) showed significantly different results in alpha diversity and taxonomic relative abundances compared to invasive samples. Overall, non-invasive samples showed decreased alpha diversity compared to intestinal samples, but the alpha diversities of fecal samples were more comparable to the intestinal samples. On the contrary, the cloacal swabs characterized significantly lower alpha diversities than in intestinal samples, but the taxonomic relative abundances acquired from cloacal swabs were similar to the intestinal samples. Phylogenetic status, diet, and domestication degree of host birds also influenced the differences in microbiota characterization between invasive and non-invasive samples. Our results indicate a general pattern in microbiota differences among intestinal mucosal and non-invasive samples across multiple bird taxa, while highlighting the importance of evaluating the appropriateness of the microbiome sampling methods used to answer specific research questions. The overall results also suggest the potential importance of using both fecal and cloacal swab sampling together to properly characterize bird microbiomes.

Keywords

Cloacal swabsAvian microbiomesFecal samplesIntestinal samplesMeta regressions

References

 

Albenberg, L., Esipova, T.V., Judge, C.P., Bittinger, K., Chen, J., Laughlin, A., et al., 2014. Correlation between intraluminal oxygen gradient and radial partitioning of intestinal microbiota. Gastroenterology 147, 1055-1063.e8.
Crossref Google Scholar
 

Andreani, N.A., Donaldson, C.J., Goddard, M., 2020. A reasonable correlation between cloacal and cecal microbiomes in broiler chickens. Poultry Sci. 99, 6062–6070.
Crossref Google Scholar
 

Balduzzi, S., Rücker, G., Schwarzer, G., 2019. How to perform a meta-analysis with R: a practical tutorial. Evid. Base Ment. Health 22, 153–160.
Crossref Google Scholar
 

Benson, A.K., Kelly, S.A., Legge, R., Ma, F., Low, S.J., Kim, J., et al., 2010. Individuality in gut microbiota composition is a complex polygenic trait shaped by multiple environmental and host genetic factors. Proc. Natl. Acad. Sci. U.S.A. 107, 18933–18938.
Crossref Google Scholar
 

Berlow, M., Kohl, K.D., Derryberry, E.P., 2020. Evaluation of non-lethal gut microbiome sampling methods in a passerine bird. Ibis 162, 911–923.
Crossref Google Scholar
 

Bodawatta, K.H., Freiberga, I., Puzejova, K., Sam, K., Poulsen, M., Jønsson, K.A., 2021a. Flexibility and resilience of great tit (Parus major) gut microbiomes to changing diets. Anim Microbiome. 3, 20.
Crossref Google Scholar
 

Bodawatta, K.H., Hird, S.M., Grond, K., Poulsen, M., Jønsson, K.A., 2022a. Avian gut microbiomes taking flight. Trends Microbiol. 30, 268–280.
Crossref Google Scholar
 

Bodawatta, K.H., Klečková, I., Klečka, J., Pužejová, K., Koane, B., Poulsen, M., et al., 2022b. Specific gut bacterial responses to natural diets of tropical birds. Sci. Rep. 12, 713.
Crossref Google Scholar
 

Bodawatta, K.H., Koane, B., Maiah, G., Sam, K., Poulsen, M., Jønsson, K.A., 2021b. Species-specific but not phylosymbiotic gut microbiomes of New Guinean passerine birds are shaped by diet and flight-associated gut modifications. Proc. R. Soc. B 288, 20210446.
Crossref Google Scholar
 

Bodawatta, K.H., Puzejova, K., Sam, K., Poulsen, M., Jønsson, K.A., 2020. Cloacal swabs and alcohol bird specimens are good proxies for compositional analyses of gut microbial communities of Great tits (Parus major). Anim. Microbiome. 2, 9.
Crossref Google Scholar
 

Bodawatta, K.H., Sam, K., Jønsson, K.A., Poulsen, M., 2018. Comparative analyses of the digestive tract microbiota of new guinean passerine birds. Front. Microbiol. 9, 1830.
Crossref Google Scholar
 

Bolyen, E., Rideout, J.R., Dillon, M.R., Bokulich, N.A., Abnet, C.C., Al-Ghalith, G.A., et al., 2019. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat. Biotechnol. 37, 852–857.
Crossref Google Scholar
 

Bryson, V., Vogel, H.J., 1965. Evolving genes and proteins. Science 147, 68–71.
Crossref Google Scholar
 

Budding, A.E., Grasman, M.E., Eck, A., Bogaards, J.A., Vandenbroucke-Grauls, C.M., van Bodegraven, A.A., et al., 2014. Rectal swabs for analysis of the intestinal microbiota. PLoS One 9, e101344.
Crossref Google Scholar
 

Capunitan, D.C., Johnson, O., Terrill, R.S., Hird, S.M., 2020. Evolutionary signal in the gut microbiomes of 74 bird species from Equatorial Guinea. Mol. Ecol. 29, 829–847.
Crossref Google Scholar
 

Clench, M.H., 1999. The avian cecum: Update and motility review. J. Exp. Zool. 283, 441–447.
Crossref Google Scholar
 

Crisol-Martínez, E., Moreno-Moyano, L.T., Wilkinson, N., Prasai, T., Brown, P.H., Moore, R.J., et al., 2016. A low dose of an organophosphate insecticide causes dysbiosis and sex-dependent responses in the intestinal microbiota of the Japanese quail (Coturnix japonica). PeerJ 4, e2002.
Crossref Google Scholar
 

Das, Q., Islam, M.R., Lepp, D., Tang, J., Yin, X., Mats, L., et al., 2020. Gut microbiota, blood metabolites, and spleen immunity in broiler chickens fed berry pomaces and phenolic-enriched extractives. Front. Vet. Sci. 7, 150.
Crossref Google Scholar
 

David, L.A., Maurice, C.F., Carmody, R.N., Gootenberg, D.B., Button, J.E., Wolfe, B.E., et al., 2014. Diet rapidly and reproducibly alters the human gut microbiome. Nature 505, 559–563.
Crossref Google Scholar
 

Davidson, G.L., Wiley, N., Cooke, A.C., Johnson, C.N., Fouhy, F., Reichert, M.S., et al., 2020. Diet induces parallel changes to the gut microbiota and problem solving performance in a wild bird. Sci. Rep. 10, 20783.
Crossref Google Scholar
 

DeSantis, T.Z., Hugenholtz, P., Larsen, N., Rojas, M., Brodie, E.L., Keller, K., et al., 2006. Greengenes, a Chimera-Checked 16S rRNA Gene Database and Workbench Compatible with ARB. Appl. Environ. Microbiol. 72, 5069–5072.
Crossref Google Scholar
 

Ding, J., Dai, R., Yang, L., He, C., Xu, K., Liu, S., et al., 2017. Inheritance and establishment of gut microbiota in chickens. Front. Microbiol. 8, 1967.
Crossref Google Scholar
 

Drovetski, S.V., O’Mahoney, M.J.V., Matterson, K.O., Schmidt, B.K., Graves, G.R., 2019. Distinct microbiotas of anatomical gut regions display idiosyncratic seasonal variation in an avian folivore. Anim. Microbiome 1, 2.
Crossref Google Scholar
 

Efthimiou, O., Debray, T.P.A., van Valkenhoef, G., Trelle, S., Panayidou, K., Moons, K.G.M., et al., 2016. GetReal in network meta-analysis: a review of the methodology. Res. Synth. Methods 7, 236–263.
Crossref Google Scholar
 
Gerta, R., Ulrike, K., Jochem, K., Orestis, E., Annabel, D., Theodoros, P., et al., 2021. Netmeta: Network Meta-Analysis Using Frequentist Methods. R Package Version 2.0- 1. https://CRAN.R-project.org/package=netmeta.
 

Godon, J.J., Arulazhagan, P., Steyer, J.P., Hamelin, J., 2016. Vertebrate bacterial gut diversity: size also matters. BMC Ecol. 16, 12.
Crossref Google Scholar
 

Grond, K., Sandercock, B.K., Jumpponen, A., Zeglin, L.H., 2018. The avian gut microbiota: community, physiology and function in wild birds. J. Avian Biol. 49, e01788.
Crossref Google Scholar
 

Groussin, M., Mazel, F., Sanders, J.G., Smillie, C.S., Lavergne, S., Thuiller, W., et al., 2017. Unraveling the processes shaping mammalian gut microbiomes over evolutionary time. Nat. Commun. 8, 14319.
Crossref Google Scholar
 

Higgins, J.P.T., Thompson, S.G., 2002. Quantifying heterogeneity in a meta-analysis. Stat. Med. 21, 1539–1558.
Crossref Google Scholar
 

Higgins, J.P.T., Thompson, S.G., Deeks, J.J., Altman, D.G., 2003. Measuring inconsistency in meta-analyses. BMJ 327, 557–560.
Crossref Google Scholar
 

Hird, S.M., Sánchez, C., Carstens, B.C., Brumfield, R.T., 2015. Comparative gut microbiota of 59 neotropical bird species. Front. Microbiol. 6, 1403.
Crossref Google Scholar
 

Ho, N.T., Li, F., Lee-Sarwar, K.A., Tun, H.M., Brown, B.P., Pannaraj, P.S., et al., 2018. Meta-analysis of effects of exclusive breastfeeding on infant gut microbiota across populations. Nat. Commun. 9, 4169.
Crossref Google Scholar
 

Hong, P.Y., Wheeler, E., Cann, I.K.O., Mackie, R.I., 2011. Phylogenetic analysis of the fecal microbial community in herbivorous land and marine iguanas of the Galapagos Islands using 16S rRNA-based pyrosequencing. ISME J 5, 1461–1470.
Crossref Google Scholar
 

Ingala, M.R., Simmons, N.B., Wultsch, C., Krampis, K., Speer, K.A., Perkins, S.L., 2018. Comparing microbiome sampling methods in a wild mammal: Fecal and intestinal samples record different signals of host ecology, evolution. Front. Microbiol. 9, 803.
Crossref Google Scholar
 

Jetz, W., Thomas, G.H., Joy, J.B., Hartmann, K., Mooers, A.O., 2012. The global diversity of birds in space and time. Nature 491, 444–448.
Crossref Google Scholar
 

Jones, R.B., Zhu, X., Moan, E., Murff, H.J., Ness, R.M., Seidner, D.L., et al., 2018. Inter-niche and inter-individual variation in gut microbial community assessment using stool, rectal swab, and mucosal samples. Sci. Rep. 8, 4139.
Crossref Google Scholar
 

Kang, K., Hu, Y., Wu, S., Shi, S., 2021. Comparative metagenomic analysis of chicken gut microbial community, function, and resistome to evaluate noninvasive and cecal sampling resources. Animals 11, 1718.
Crossref Google Scholar
 

Kembel, S.W., Cowan, P.D., Helmus, M.R., Cornwell, W.K., Morlon, H., Ackerly, D.D., et al., 2010. Picante: R tools for integrating phylogenies and ecology. Bioinformatics 26, 1463–1464.
Crossref Google Scholar
 

Lee, S.J., Cho, S., La, T.M., Lee, H.J., Lee, J.B., Park, S.Y., et al., 2020. Comparison of microbiota in the cloaca, colon, and magnum of layer chicken. PLoS One 15, e0237108.
Crossref Google Scholar
 

Lees, A.C., Haskell, L., Allinson, T., Bezeng, S.B., Burfield, I.J., Renjifo, L.M., et al., 2022. State of the World's Birds. Annu. Rev. Environ. Resour. 47, 231–260.
Crossref Google Scholar
 

Ley, R.E., Lozupone, C.A., Hamady, M., Knight, R., Gordon, J.I., 2008. Worlds within worlds: evolution of the vertebrate gut microbiota. Nat. Rev. Microbiol. 6, 776–788.
Crossref Google Scholar
 

Li, C., Liu, Y., Gong, M., Zheng, C., Zhang, C., Li, H., et al., 2021. Diet-induced microbiome shifts of sympatric overwintering birds. Appl. Microbiol. Biotechnol. 105, 5993–6005.
Crossref Google Scholar
 

Liu, G., Meng, D., Gong, M., Li, H., Wen, W., Wang, Y., et al., 2020. Effects of sex and diet on gut microbiota of farmland-dependent wintering birds. Front. Microbiol. 11, 587873.
Crossref Google Scholar
 

Liu, J., Stewart, S.N., Robinson, K., Yang, Q., Lyu, W., Whitmore, M.A., et al., 2021. Linkage between the intestinal microbiota and residual feed intake in broiler chickens. J. Anim. Sci. Biotechnol. 12, 22.
Crossref Google Scholar
 

Oakley, B.B., Kogut, M.H., 2016. Spatial and temporal changes in the broiler chicken cecal and fecal microbiomes and correlations of bacterial taxa with cytokine gene expression. Front. Vet. Sci. 3, 11.
Crossref Google Scholar
 

Pauwels, J., Taminiau, B., Janssens, G.P., De Beenhouwer, M., Delhalle, L., Daube, G., et al., 2015. Cecal drop reflects the chickens' cecal microbiome, fecal drop does not. J. Microbiol. Methods 117, 164–170.
Crossref Google Scholar
 

Peters, J.L., Sutton, A.J., Jones, D.R., Abrams, K.R., Rushton, L., 2006. Comparison of two methods to detect publication bias in meta-analysis. JAMA 295, 676–680.
Crossref Google Scholar
 

Peters, J.L., Sutton, A.J., Jones, D.R., Abrams, K.R., Rushton, L., 2008. Contour-enhanced meta-analysis funnel plots help distinguish publication bias from other causes of asymmetry. J. Epidemiol. 61, 991–996.
Crossref Google Scholar
 

Pigot, A.L., Sheard, C., Miller, E.T., Bregman, T.P., Freeman, B.G., Roll, U., et al., 2020. Macroevolutionary convergence connects morphological form to ecological function in birds. Nat. Ecol. Evol. 4, 230–239.
Crossref Google Scholar
 

Pillinger, T., McCutcheon, R.A., Vano, L., Mizuno, Y., Arumuham, A., Hindley, G., et al., 2020. Comparative effects of 18 antipsychotics on metabolic function in patients with schizophrenia, predictors of metabolic dysregulation, and association with psychopathology: a systematic review and network meta-analysis. Lancet Psychiatry 7, 64–77.
Crossref Google Scholar
 

Pradhan, A.D., 2014. Sex Differences in the metabolic syndrome: implications for cardiovascular health in women. Clin. Chem. 60, 44–52.
Crossref Google Scholar
 
R Core Team, 2021. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/.
 

Ramakrishna, B.S., 2013. Role of the gut microbiota in human nutrition and metabolism. J. Gastroenterol. Hepatol. 28, 9–17.
Crossref Google Scholar
 

Rothschild, D., Weissbrod, O., Barkan, E., Kurilshikov, A., Korem, T., Zeevi, D., et al., 2018. Environment dominates over host genetics in shaping human gut microbiota. Nature 555, 210–215.
Crossref Google Scholar
 

Salanti, G., Del Giovane, C., Chaimani, A., Caldwell, D.M., Higgins, J.P.T., 2014. Evaluating the quality of evidence from a network meta-analysis. PLoS One 9, e99682.
Crossref Google Scholar
 

Sekercioglu, C.H., 2006. Increasing awareness of avian ecological function. Trends Ecol. Evol. 21, 464–471.
Crossref Google Scholar
 

Siegerstetter, S.C., Schmitz-Esser, S., Magowan, E., Wetzels, S.U., Zebeli, Q., Lawlor, P.G., et al., 2017. Intestinal microbiota profiles associated with low and high residual feed intake in chickens across two geographical locations. PLoS One 12, e0187766.
Crossref Google Scholar
 

Singh, R.K., Chang, H.W., Yan, D., Lee, K.M., Ucmak, D., Wong, K., et al., 2017. Influence of diet on the gut microbiome and implications for human health. J. Transl. Med. 15, 73.
Crossref Google Scholar
 

Song, S.J., Sanders, J.G., Delsuc, F., Metcalf, J., Amato, K., Taylor, M.W., et al., 2020. Comparative analyses of vertebrate gut microbiomes reveal convergence between birds and bats. mBio 11, e02901–02919.
Crossref Google Scholar
 

Stanley, D., Geier, M.S., Chen, H., Hughes, R.J., Moore, R.J., 2015. Comparison of fecal and cecal microbiotas reveals qualitative similarities but quantitative differences. BMC Microbiol. 15, 51.
Crossref Google Scholar
 

Stanley, T.D., Doucouliagos, H., 2014. Meta-regression approximations to reduce publication selection bias. Res. Synth. Methods 5, 60–78.
Crossref Google Scholar
 

Stearns, J.C., Zulyniak, M.A., de Souza, R.J., Campbell, N.C., Fontes, M., Shaikh, M., et al., 2017. Ethnic and diet-related differences in the healthy infant microbiome. Genome Med. 9, 32.
Crossref Google Scholar
 

Sullam, K.E., Essinger, S.D., Lozupone, C.A., O’connor, M.P., Rosen, G.L., Knight, R., et al., 2012. Environmental and ecological factors that shape the gut bacterial communities of fish: a meta-analysis. Mol. Ecol. 21, 3363–3378.
Crossref Google Scholar
 

Sun, S., Zhu, X., Huang, X., Murff, H.J., Ness, R.M., Seidner, D.L., et al., 2021. On the robustness of inference of association with the gut microbiota in stool, rectal swab and mucosal tissue samples. Sci. Rep. 11, 14828.
Crossref Google Scholar
 

Trevelline, B.K., Sosa, J., Hartup, B.K., Kohl, K.D., 2020. A bird's-eye view of phylosymbiosis: weak signatures of phylosymbiosis among all 15 species of cranes. Proc. Royal Soc. B 287, 20192988.
Crossref Google Scholar
 

Videvall, E., Strandh, M., Engelbrecht, A., Cloete, S., Cornwallis, C.K., 2018. Measuring the gut microbiome in birds: Comparison of faecal and cloacal sampling. Mol. Ecol. Resour. 18, 424–434.
Crossref Google Scholar
 

Viechtbauer, W., 2010. Conducting meta-analyses in r with the metafor package. J. Stat. Softw. 36, 1–48.
Crossref Google Scholar
 

Waite, D.W., Taylor, M.W., 2014. Characterizing the avian gut microbiota: membership, driving influences, and potential function. Front. Microbiol. 5, 223.
Crossref Google Scholar
 

Wen, C., Yan, W., Sun, C., Ji, C., Zhou, Q., Zhang, D., et al., 2019. The gut microbiota is largely independent of host genetics in regulating fat deposition in chickens. ISME J 13, 1422–1436.
Crossref Google Scholar
 
Wickham, H., 2016. ggplot2: Elegant Graphics for Data Analysis. Springer, New York, NY. https://ggplot2.tidyverse.org.
Crossref
 

Wilkinson, N., Hughes, R.J., Aspden, W.J., Chapman, J., Moore, R.J., Stanley, D., 2016. The gastrointestinal tract microbiota of the Japanese quail, Coturnix japonica. Appl. Microbiol. Biotechnol. 100, 4201–4209.
Crossref Google Scholar
 

Williams, T., Athrey, G., 2020. Cloacal swabs are unreliable sources for estimating lower gastro-intestinal tract microbiota membership and structure in broiler chickens. Microorganisms 8, 718.
Crossref Google Scholar
 

Wu, G.D., Chen, J., Hoffmann, C., Bittinger, K., Chen, Y.Y., Keilbaugh, S.A., et al., 2011. Linking long-term dietary patterns with gut microbial enterotypes. Science 334, 105–108.
Crossref Google Scholar
 

Xu, J., Lawley, B., Wong, G., Otal, A., Chen, L., Ying, T.J., et al., 2020a. Ethnic diversity in infant gut microbiota is apparent before the introduction of complementary diets. Gut Microbes 11, 1362–1373.
Crossref Google Scholar
 
Xu, L.L., Chen, H., Zhang, M., Zhu, W., Chang, Q., Lu, G., et al., 2020b. Changes in the community structure of the symbiotic microbes of wild amphibians from the eastern edge of the Tibetan Plateau Microbiol 9, e1004.
Crossref
 

Xu, Q., Yuan, X., Gu, T., Li, Y., Dai, W., Shen, X., et al., 2017. Comparative characterization of bacterial communities in geese fed all-grass or high-grain diets. PLoS One 12, e0185590.
Crossref Google Scholar
 

Yan, W., Sun, C., Yuan, J., Yang, N., 2017. Gut metagenomic analysis reveals prominent roles of Lactobacillus and cecal microbiota in chicken feed efficiency. Sci. Rep. 7, 45308.
Crossref Google Scholar
 

Yan, W., Sun, C., Zheng, J., Wen, C., Ji, C., Zhang, D., et al., 2019. Efficacy of fecal sampling as a gut proxy in the study of chicken gut microbiota. Front. Microbiol. 10, 2126.
Crossref Google Scholar
 

Yang, Z., Rannala, B., 2005. Bayesian estimation of species divergence times under a molecular clock using multiple fossil calibrations with soft bounds. Mol. Biol. Evol. 23, 212–226.
Crossref Google Scholar
 

Youngblut, N.D., Reischer, G.H., Dauser, S., Maisch, S., Walzer, C., Stalder, G., et al., 2021. Vertebrate host phylogeny influences gut archaeal diversity. Nat. Microbiol. 6, 1443–1454.
Crossref Google Scholar
 

Youngblut, N.D., Reischer, G.H., Walters, W., Schuster, N., Walzer, C., Stalder, G., et al., 2019. Host diet and evolutionary history explain different aspects of gut microbiome diversity among vertebrate clades. Nat. Commun. 10, 2200.
Crossref Google Scholar
 

Zhang, Y., Simon, S.E., Johnson, J.A., Allen, M.S., 2017. Spatial microbial composition along the gastrointestinal tract of captive attwater's prairie chicken. Microb. Ecol. 73, 966–977.
Crossref Google Scholar
Avian Research
Volume 14 Issue 2,
June 2023
Article number: 100086
DOI: 10.1016/j.avrs.2023.100086
Cite this article:
Zhou T, Bodawatta KH, Jiang A. A network meta-analysis on comparison of invasive and non-invasive sampling methods to characterize intestinal microbiota of birds. Avian Research, 2023, 14(2): 100086. https://doi.org/10.1016/j.avrs.2023.100086

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Received: 08 September 2022
Revised: 12 February 2023
Accepted: 12 February 2023
Published: 15 February 2023
© 2023 The Authors.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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