Abstract
Gut microbiota have long attracted the interest of scientists due to their profound impact on the well-being of animals. A non-random pattern of microbial assembly that results in a parallelism between host phylogeny and microbial similarity is described as phylosymbiosis. Phylosymbiosis has been consistently observed in different clades of animal hosts, but there have been no studies on crustaceans. In this study, we investigated whether host phylogeny has an impact on the gut microbiota assemblages in decapod shrimps. We examined the gut microbial communities in 20 shrimp species from three families inhabiting distinct environments, using metabarcoding analyses of the V1–V3 hypervariable region of the 16S rRNA gene. Gut microbial communities varied within each shrimp group but were generally dominated by Proteobacteria. A prevalent phylosymbiotic pattern in shrimps was evidenced for the first time by the observations of (1) the distinguishability of microbial communities among species within each group, (2) a significantly lower intraspecific than interspecific gut microbial beta diversity across shrimp groups, (3) topological congruence between host phylogenetic trees and gut microbiota dendrograms, and (4) a correlation between host genetic distances and microbial dissimilarities. Consistent signals of phylosymbiosis were observed across all groups in dendrograms based on the unweighted UniFrac distances at 99% operational taxonomic units (OTUs) level and in Mantel tests based on the weighted UniFrac distances based on 97% OTUs and amplicon sequence variants. Penaeids exhibited phylosymbiosis in most tests, while phylosymbiotic signals in atyids and pandalids were only detected in fewer than half of the tests. A weak phylogenetic signal was detected in the predicted functions of the penaeid gut microbiota. However, the functional diversities of the two caridean groups were not significantly related to host phylogeny. Our observations of a parallelism in the taxonomy of the gut microbiota with host phylogeny for all shrimp groups examined and in the predicted functions for the penaeid shrimps indicate a tight host-microbial relationship during evolution.
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Data Availability
Sequences used for host phylogeny construction were deposited in the NCBI Nucleotide database with accession numbers MT540493-MT540497 (for atyid 16S rRNA), MT553844-MT553853 (for atyid NaK and enolase), and MT540544-MT540551 (for pandalid 16S rRNA). Raw reads of metabarcoding sequencing are available in the NCBI Sequence Read Archive under the Bioproject accession PRJNA635372.
Change history
21 August 2021
A Correction to this paper has been published: https://doi.org/10.1007/s00248-021-01825-5
References
Clemente JC, Ursell LK, Parfrey LW, Knight R (2012) The impact of the gut microbiota on human health: an integrative view. Cell 148:1258–1270. https://doi.org/10.1016/j.cell.2012.01.035
Sommer F, Bäckhed F (2013) The gut microbiota - masters of host development and physiology. Nat Rev Microbiol 11:227–238
Walter J, Ley R (2011) The human gut microbiome: ecology and recent evolutionary changes. Annu Rev Microbiol 65:411–429. https://doi.org/10.1146/annurev-micro-090110-102830
Brooks AW, Kohl KD, Brucker RM, van Opstal EJ, Bordenstein SR (2016) Phylosymbiosis: relationships and functional effects of microbial communities across host evolutionary history. Plos Biol 14:e2000225. https://doi.org/10.1371/journal.pbio.2000225
Bourguignon T, Lo N, Dietrich C et al (2018) Rampant host switching shaped the termite gut microbiome. Curr Biol 28:649–654.e2. https://doi.org/10.1016/j.cub.2018.01.035
Ross AA, Müller KM, Weese JS, Neufeld JD (2018) Comprehensive skin microbiome analysis reveals the uniqueness of human skin and evidence for phylosymbiosis within the class Mammalia. Proc Natl Acad Sci USA 115:E5786–E5795. https://doi.org/10.1073/pnas.1801302115
Javůrková VG, Kreisinger J, Procházka P, Požgayová M, Ševčíková K, Brlík V, Adamík P, Heneberg P, Porkert J (2019) Unveiled feather microcosm: feather microbiota of passerine birds is closely associated with host species identity and bacteriocin-producing bacteria. ISME J 13:2363–2376. https://doi.org/10.1038/s41396-019-0438-4
Lim SJ, Bordenstein SR (2020) An introduction to phylosymbiosis. Proc Biol Sci 287:20192900. https://doi.org/10.1098/rspb.2019.2900
Moran NA, Sloan DB (2015) The hologenome concept: helpful or hollow? Plos Biol 13:e1002311
van Opstal EJ, Bordenstein SR (2019) Phylosymbiosis impacts adaptive traits in Nasonia wasps. mBio 10(4):e00887–e00819
Titus BM, Laroche R, Rodríguez E, Wirshing H, Meyer CP (2020) Host identity and symbiotic association affects the taxonomic and functional diversity of the clownfish-hosting sea anemone microbiome. Biol Lett 16:20190738. https://doi.org/10.1098/rsbl.2019.0738
Trevelline BK, Sosa J, Hartup BK, Kohl KD (2020) A bird’s-eye view of phylosymbiosis: weak signatures of phylosymbiosis among all 15 species of cranes. P Roy Soc B-Biol Sci 287:20192988
Lutz HL, Jackson EW, Webala PW et al (2019) Ecology and host identity outweigh evolutionary history in shaping the bat microbiome. mSystems 4(6). https://doi.org/10.1128/mSystems.00511-19
Song SJ, Sanders JG, Delsuc F, et al (2020) Comparative analyses of vertebrate gut microbiomes reveal convergence between birds and bats. mBio 25;11(1). https://doi.org/10.1128/mBio.02901-19
De Grave N. Dean Pentcheff Shane T. Ahyong Tin-Yam Chan S (2009) A classification of living and fossil genera of decapod crustaceans. Raffles Bull Zool 21:1–109
Boudreau SA, Worm B (2012) Ecological role of large benthic decapods in marine ecosystems: a review. Mar Ecol Prog Ser 469:195–213
De Grave S, C H J (2011) Carideorum catalogus: the recent species of the Dendrobranchiate, Stenopodidean, Procarididean and Caridean shrimps (Crustacea: Decapoda). Leiden: NCB Naturalis
Farfante IP, Kensley BF (1997) Penaeoid and Sergestoid shrimps and prawns of the world: keys and diagnoses for the families and genera. Mem Mus Natl Hist Nat 175:233
Li E, Xu C, Wang X, Wang S, Zhao Q, Zhang M, Qin JG, Chen L (2018) Gut microbiota and its modulation for healthy farming of pacific white shrimp Litopenaeus vannamei. Rev Fish Sci Aquac 26:381–399
Simon CJ, Truong HH, Noble TH, Osborne SA, Wynne JW, Wade NM (2020) Microbial biomass, marine invertebrate meals and feed restriction influence the biological and gut microbiota response of shrimp Penaeus monodon. Aquaculture 520:734679
Holt CC, Bass D, Stentiford GD, van der Giezen M (2020) Understanding the role of the shrimp gut microbiome in health and disease. J Invertebr Pathol 21:107387. https://doi.org/10.1016/j.jip.2020.107387
Farzanfar A (2006) The use of probiotics in shrimp aquaculture. FEMS Immunol Med Microbiol 48(2):149–158
Cheung MK, Yip HY, Nong W, PTW L, Chu KH, Kwan HS, JHL H (2015) Rapid change of microbiota diversity in the gut but not the hepatopancreas during gonadal development of the new shrimp model Neocaridina denticulata. Mar Biotechnol 17:811–819
Durand L, Zbinden M, Cueff-Gauchard V et al (2010) Microbial diversity associated with the hydrothermal shrimp Rimicaris exoculata gut and occurrence of a resident microbial community. FEMS Microbiol Ecol 71:291–303. https://doi.org/10.1111/j.1574-6941.2009.00806.x
Durand L, Roumagnac M, Cueff-Gauchard V et al (2015) Biogeographical distribution of Rimicaris exoculata resident gut epibiont communities along the Mid-Atlantic Ridge hydrothermal vent sites. FEMS Microbiol Ecol 91(10):fiv101. https://doi.org/10.1093/femsec/fiv101
Tzeng T-D, Pao Y-Y, Chen P-C, FCH W, Jean WD, Wang D (2015) Effects of host phylogeny and habitats on gut microbiomes of oriental river prawn (Macrobrachium nipponense). Plos One 10:e0132860. https://doi.org/10.1371/journal.pone.0132860
Rothschild D, Weissbrod O, Barkan E, Kurilshikov A, Korem T, Zeevi D, Costea PI, Godneva A, Kalka IN, Bar N, Shilo S, Lador D, Vila AV, Zmora N, Pevsner-Fischer M, Israeli D, Kosower N, Malka G, Wolf BC, Avnit-Sagi T, Lotan-Pompan M, Weinberger A, Halpern Z, Carmi S, Fu J, Wijmenga C, Zherna (2018) Environment dominates over host genetics in shaping human gut microbiota. Nature 555:210–215. https://doi.org/10.1038/nature25973
Ma KY, Chan T-Y, Chu KH (2011) Refuting the six-genus classification of Penaeus s.l. (Dendrobranchiata, Penaeidae): a combined analysis of mitochondrial and nuclear genes. Zoologica Scripta 40:498–508
Katoh K, Rozewicki J, Yamada KD (2019) MAFFT online service: multiple sequence alignment, interactive sequence choice and visualization. Brief Bioinform 20:1160–1166. https://doi.org/10.1093/bib/bbx108
Hoang DT, Vinh LS, Flouri T, Stamatakis A, von Haeseler A, Minh BQ (2018) MPBoot: fast phylogenetic maximum parsimony tree inference and bootstrap approximation. BMC Evol Biol 18:11. https://doi.org/10.1186/s12862-018-1131-3
Miller MA, Pfeiffer W, Schwartz T (2010) Creating the CIPRES Science Gateway for inference of large phylogenetic trees. 2010 Gateway Computing Environments Workshop (GCE)
Consortium THMP, The human microbiome project consortium (2012) A framework for human microbiome research. Nature 486:215–221
Caporaso JG, Lauber CL, Walters WA, Berg-Lyons D, Huntley J, Fierer N, Owens SM, Betley J, Fraser L, Bauer M, Gormley N, Gilbert JA, Smith G, Knight R (2012) Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J 6:1621–1624. https://doi.org/10.1038/ismej.2012.8
Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, Fierer N, Peña AG, Goodrich JK, Gordon JI, Huttley GA, Kelley ST, Knights D, Koenig JE, Ley RE, Lozupone CA, McDonald D, Muegge BD, Pirrung M, Reeder J, Sevinsky JR, Turnbaugh PJ, Walters WA, Widmann J, Yatsunenko T (2010) QIIME allows analysis of high-throughput community sequencing data. Nat Methods 7:335–336. https://doi.org/10.1038/nmeth.f.303
Bolyen E, Rideout JR, Dillon MR, Bokulich NA, Abnet CC, al-Ghalith GA, Alexander H, Alm EJ, Arumugam M, Asnicar F, Bai Y, Bisanz JE, Bittinger K, Brejnrod A, Brislawn CJ, Brown CT, Callahan BJ, Caraballo-Rodríguez AM, Chase J, Cope EK, da Silva R, Diener C, Dorrestein PC, Douglas GM, Durall DM, Duvallet C, Edwardson CF, Ernst M, Estaki M, Fouquier J, Gauglitz JM, Gibbons SM, Gibson DL, Gonzalez A, Gorlick K, Guo J, Hillmann B, Holmes S, Holste H, Huttenhower C, Huttley GA, Janssen S, Jarmusch AK, Jiang L, Kaehler BD, Kang KB, Keefe CR, Keim P, Kelley ST, Knights D, Koester I, Kosciolek T, Kreps J, MGI L, Lee J, Ley R, Liu YX, Loftfield E, Lozupone C, Maher M, Marotz C, Martin BD, McDonald D, LJ MI, Melnik AV, Metcalf JL, Morgan SC, Morton JT, Naimey AT, Navas-Molina JA, Nothias LF, Orchanian SB, Pearson T, Peoples SL, Petras D, Preuss ML, Pruesse E, Rasmussen LB, Rivers A, Robeson II MS, Rosenthal P, Segata N, Shaffer M, Shiffer A, Sinha R, Song SJ, Spear JR, Swafford AD, Thompson LR, Torres PJ, Trinh P, Tripathi A, Turnbaugh PJ, Ul-Hasan S, der Hooft JJJ v, Vargas F, Vázquez-Baeza Y, Vogtmann E, von Hippel M, Walters W, Wan Y, Wang M, Warren J, Weber KC, CHD W, Willis AD, Xu ZZ, Zaneveld JR, Zhang Y, Zhu Q, Knight R, Caporaso JG (2019) Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat Biotechnol 37:1091. https://doi.org/10.1038/s41587-019-0252-6
RStudio Team (2020) RStudio: integrated development for R. RStudio, PBC, Boston http://www.rstudio.com/
PJ MM, Holmes S (2013) phyloseq: An R package for reproducible interactive analysis and graphics of microbiome census data. Plos One 8:e61217
Yu G, Smith DK, Zhu H, Guan Y, TTY L (2017) ggtree: an R package for visualization and annotation of phylogenetic trees with their covariates and other associated data. Methods Ecol Evol 8:28–36
Wickham H (2016) ggplot2: elegant graphics for data analysis. Springer-Verlag, New York
Navas-Molina JA, Peralta-Sánchez JM, González A et al (2013) Advancing our understanding of the human microbiome using QIIME. Methods Enzymol 531:371–444. https://doi.org/10.1016/B978-0-12-407863-5.00019-8
Langille MGI, Zaneveld J, Caporaso JG, McDonald D, Knights D, Reyes JA, Clemente JC, Burkepile DE, Vega Thurber RL, Knight R, Beiko RG, Huttenhower C (2013) Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nat Biotechnol 31:814–821. https://doi.org/10.1038/nbt.2676
Douglas GM, Maffei VJ, Zaneveld J, Yurgel SN, Brown JR, Taylor CM, Huttenhower C, Langille MG (2020) PICRUSt2 for prediction of metagenome functions. Nat Biotechnol 38(6):685–688. https://doi.org/10.1038/s41587-020-0548-6
Yu G (2020) aplot: decorate a “ggplot” with associated information. R package version 0.0.6. https://CRAN.R-project.org/package=aplot. Accessed 2020-09-03
Parks DH, Tyson GW, Hugenholtz P, Beiko RG (2014) STAMP: statistical analysis of taxonomic and functional profiles. Bioinformatics 30:3123–3124. https://doi.org/10.1093/bioinformatics/btu494
Robinson DF, Foulds LR (1981) Comparison of phylogenetic trees. Math Biosci 53:131–147
Bogdanowicz D, Giaro K (2013) On a matching distance between rooted phylogenetic trees. I J Ap Mat Com Sci 23:669–684
Paradis E, Schliep K (2019) ape 5.0: an environment for modern phylogenetics and evolutionary analyses in R. Bioinformatics 35:526–528
Dixon P (2003) VEGAN, a package of R functions for community ecology. J Veg Sci 14:927–930
Zhang Z, Xu D, Wang L, Hao J, Wang J, Zhou X, Wang W, Qiu Q, Huang X, Zhou J, Long R, Zhao F, Shi P (2016) Convergent evolution of rumen microbiomes in high-altitude mammals. Curr Biol 26:1873–1879. https://doi.org/10.1016/j.cub.2016.05.012
Cardona E, Gueguen Y, Magré K, Lorgeoux B, Piquemal D, Pierrat F, Noguier F, Saulnier D (2016) Bacterial community characterization of water and intestine of the shrimp Litopenaeus stylirostris in a biofloc system. BMC Microbiol 16(1):157
Wei H, Wang H, Tang L, Mu C, Ye C, Chen L, Wang C (2019) High-throughput sequencing reveals the core gut microbiota of the mud crab (Scylla paramamosain) in different coastal regions of southern China. BMC Genomics 20:829. https://doi.org/10.1186/s12864-019-6219-7
Shui Y, Guan Z-B, Liu G-F, Fan L-M (2020) Gut microbiota of red swamp crayfish Procambarus clarkii in integrated crayfish-rice cultivation model. AMB Express 10:5. https://doi.org/10.1186/s13568-019-0944-9
Ooi MC, Goulden EF, Smith GG et al (2017) Developmental and gut-related changes to microbiomes of the cultured juvenile spiny lobster Panulirus ornatus. FEMS Microbiol Ecol 93(12):fix159. https://doi.org/10.1093/femsec/fix159
Mazel F, Davis KM, Loudon A, et al (2018) Is host filtering the main driver of phylosymbiosis across the tree of life? mSystems 3(5). https://doi.org/10.1128/mSystems.00097-18
Tinker KA, Ottesen EA (2020) Phylosymbiosis across deeply diverging lineages of omnivorous cockroaches (order Blattodea). Appl Environ Microbiol 86(7). https://doi.org/10.1128/AEM.02513-19
O’Brien PA, Tan S, Yang C, Frade PR, Andreakis N, Smith HA, Miller DJ, Webster NS, Zhang G, Bourne DG (2020) Diverse coral reef invertebrates exhibit patterns of phylosymbiosis. ISME J 14:2211–2222. https://doi.org/10.1038/s41396-020-0671-x
Van Dover CL, Fry B, Grassle JF et al (1988) Feeding biology of the shrimp Rimicaris exoculata at hydrothermal vents on the Mid-Atlantic Ridge. Mar Biol 98:209–216
Pond DW, Dixon DR, Bell MV, Fallick AE, Sargent JR (1997) Occurrence of 16:2(n-4) and 18:2(n-4) fatty acids in the lipids of the hydrothermal vent shrimps Rimicaris exoculata and Alvinocaris markensis: nutritional and trophic implications. Mar Ecol Prog Ser 156:167–174
Staubach F, Baines JF, Künzel S, Bik EM, Petrov DA (2013) Host species and environmental effects on bacterial communities associated with Drosophila in the laboratory and in the natural environment. Plos One 8:e70749. https://doi.org/10.1371/journal.pone.0070749
Franzenburg S, Walter J, Künzel S et al (2013) Distinct antimicrobial peptide expression determines host species-specific bacterial associations. Proc Natl Acad Sci USA 110:E3730–E3738. https://doi.org/10.1073/pnas.1304960110
Sanders JG, Powell S, Kronauer DJC, Vasconcelos HL, Frederickson ME, Pierce NE (2014) Stability and phylogenetic correlation in gut microbiota: lessons from ants and apes. Mol Ecol 23:1268–1283. https://doi.org/10.1111/mec.12611
Acknowledgements
We thank T.Y. Chan, National Taiwan Ocean University, for his support to our field trip in collecting the pandalid samples; L.M. Tsang, The Chinese University of Hong Kong, for providing information on sample collection; and T.T. Tsang, The Chinese University of Hong Kong, for assistance in PICRUSt2 analyses. David Wilmshurst edited the final version of the manuscript.
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This work was supported by grants from the Collaborative Research Fund (project no. C4042-14G) of the Research Grants Council, Hong Kong SAR Government and the Hong Kong Branch of Southern Marine Science and Technology Guangdong Laboratory (Guangzhou), China.
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K.H. Chu, Y. Tang, and K.Y. Ma designed and conceived the idea. Y. Tang conducted the experiments, analyzed the data, and wrote the manuscript. M.K. Cheung provided suggestions for data analyses. C.-H. Yang provided the 16S rRNA gene sequences of pandalids. X. Hu and Y. Wang assisted sample collection. K.Y. Ma, M.K. Cheung, H.S. Kwan, and K.H. Chu revised the manuscript. K.H. Chu supervised and monitored the project.
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Supplementary Information
ESM 2
ST1 Breakdown of high-quality reads by species.
ESM 3
ST2 Importance scores of features at the bacterial genus level.
ESM 4
ST3 Descriptions of the top 10 abundant predicted functional pathways.
ESM 5
SF1 Host phylogenetic trees with outgroups.
ESM 6
SF2 Diversity and PICRUSt2 results based on 97% OTUs and ASVs.
ESM 7
SF3 Microbiota dendrograms constructed using 97% OTUs and ASVs.
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Tang, Y., Ma, K.Y., Cheung, M.K. et al. Gut Microbiota in Decapod Shrimps: Evidence of Phylosymbiosis. Microb Ecol 82, 994–1007 (2021). https://doi.org/10.1007/s00248-021-01720-z
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DOI: https://doi.org/10.1007/s00248-021-01720-z