Skip to main content

Advertisement

Log in

“Unraveling the Gut Microbiome of the Genus Herichthys (Pisces: Cichlidae): What Can We Learn from Museum Specimens?”

  • Published:
Current Microbiology Aims and scope Submit manuscript

Abstract

The use of museum preserved specimens to know microbiome in extinct and threatened species has been explored recently. The fishes of the genus Herichthys are distributed mainly in the Pánuco-Tamesí system in Northeastern Mexico, one of the most polluted basins in the country leading to near half of the species be considering as threatened. In this paper we used the hypervariable V4 region of the 16S rRNA gene from the 11 species of the genus Herichthys obtained from museum collections to evaluate the potential use of fixed preserved vouchers in the knowledge of gut microbiota diversity and the potential role of sympatric and allopatric speciation of the hosts in the gut microbiome evolution. The 100% of the samples were successfully amplified where the number of amplicons ranged from 4500 from a formaldehyde fixed specimen up to 55,000 in ethanol preserved specimens. Differences in gut microbiota were found between sympatric species and among the comparison of some trophic guilds. A non-random association between the gut host and their microbiome was found allow to suggest a potential phylosymbiosis relationship. In conclusion, the most abundant phyla recovered from the gut microbiota in this study were similar to those previously reported in other cichlids supporting the idea that a gut microbial core is conserved in this group of fishes despite millions of years of evolution and leading to support the potential use of museum specimens in microbiome studies.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Data Availability

All sequences obtained were uploaded to the NCBI database under the Bioproject number PRJNA715246.

Code Availability

Scripts used in the analysis of the above data can be found at https://github.com/HOmarMejiaG/Herichthys-microbiome.

References

  1. Nayak SK (2010) Probiotics and immunity: a fish perspective. Fish Shellfish Immunol 29:2–14. https://doi.org/10.1016/j.fsi.2010.02.017

    Article  PubMed  CAS  Google Scholar 

  2. Wang AR, Ran C, Ringø E, Zhou ZG (2018) Progress in fish gastrointestinal microbiota research. Rev Aquac 10:626–640. https://doi.org/10.1111/raq.12191

    Article  Google Scholar 

  3. Härer A, Torres-Dowdall J, Rometsch SJ, Yohannes E, Machado-Schiaffino G, Meyer A (2020) Parallel and non-parallel changes of the gut microbiota during trophic diversification in repeated young adaptive radiations of sympatric cichlid fish. Microbiome 8:149. https://doi.org/10.1186/s40168-020-00897-8

    Article  PubMed  PubMed Central  Google Scholar 

  4. Sevellec M, Derome N, Bernatchez L (2018) Holobionts and ecological speciation: the intestinal microbiota of lake whitefish species pairs. Microbiome 6:47. https://doi.org/10.1186/s40168-018-0427-2

    Article  PubMed  PubMed Central  Google Scholar 

  5. Kohl KD (2020) Ecological and evolutionary mechanisms underlying patterns of phylosymbiosis in host-associated microbial communities. Philos Trans R Soc B 375:20190251. https://doi.org/10.1098/rstb.2019.0251

    Article  CAS  Google Scholar 

  6. Lim SJ, Bordenstein SR (2020) An introduction to phylosymbiosis. Proc R Soc B 287:20192900. https://doi.org/10.7287/peerj.preprints.27879v1

    Article  PubMed  PubMed Central  Google Scholar 

  7. Suarez AV, Tsutsui ND (2004) The value of museum collections for research and society. Bioscience 54:66–74. https://doi.org/10.1641/0006-3568(2004)054[0066:tvomcf]2.0.co;2

    Article  Google Scholar 

  8. Bradley RD, Bradley LC, Garner HJ, Baker RJ (2014) Assessing the value of natural history collections and addressing issues regarding long-term growth and care. Bioscience 64:1150–1158. https://doi.org/10.1093/biosci/biu166

    Article  Google Scholar 

  9. Bodawatta KH, Puzejova K, Sam K, Poulsen M, Jønsson KA (2020) Cloacal swabs and alcohol bird specimens are good proxies for compositional analyses of gut microbial communities of Great tits (Parus major). Anim Microbiome 2:1–13. https://doi.org/10.1186/s42523-020-00026-8

    Article  Google Scholar 

  10. Heindler FM, Christiansen H, Frédérich B, Dettaï A, Lepoint G, Maes GE et al (2018) Historical DNA metabarcoding of the prey and microbiome of trematomid fishes using museum samples. Front Ecol Evol 6:151. https://doi.org/10.3389/fevo.2018.00151

    Article  Google Scholar 

  11. Klingenberg CP, Barluenga M, Meyer A (2003) Body shape variation in cichlid fishes of the Amphilophus citrinellus species complex. Biol J Linn Soc 80:397–408. https://doi.org/10.1046/j.1095-8312.2003.00246.x

    Article  Google Scholar 

  12. Schott RK, Refvik SP, Hauser FE, López-Fernández H, Chang BS (2014) Divergent positive selection in rhodopsin from lake and riverine cichlid fishes. Mol Biol Evol 31:1149–1165. https://doi.org/10.1093/molbev/msu064

    Article  PubMed  CAS  Google Scholar 

  13. Baldo L, Riera JL, Salzburger W, Barluenga M (2019) Phylogeography and ecological niche shape the cichlid fish gut microbiota in Central American and African lakes. Front Microbiol 10:2372. https://doi.org/10.3389/fmicb.2019.02372

    Article  PubMed  PubMed Central  Google Scholar 

  14. Baldo L, Pretus JL, Riera JL, Musilova Z, Nyom ARB, Salzburger W (2017) Convergence of gut microbiotas in the adaptive radiations of African cichlid fishes. ISME J 11:1975–1987. https://doi.org/10.1038/ismej.2017.62

    Article  PubMed  PubMed Central  Google Scholar 

  15. Pérez-Miranda F, Mejia O, Zúñiga G, Soto-Galera E, Říčan O (2019) Feeding ecomorphologies in the genus Herichthys (Perciformes: Cichlidae): an approximation using stomach content and lower pharyngeal jaw shapes. Rev Biol Trop 67:643–653. https://doi.org/10.1038/ismej.2017.62

    Article  Google Scholar 

  16. Pérez-Miranda F, Mejía O, Soto-Galera E, Espinosa-Pérez H, Piálek L, Říčan O (2018) Phylogeny and species diversity of the genus Herichthys (Teleostei: Cichlidae). J Zool Syst Evol Res 56:233–247. https://doi.org/10.1111/jzs.12197

    Article  Google Scholar 

  17. Pérez-Miranda F, Mejia O, López B, Říčan O (2020) Molecular clocks, biogeography and species diversity in Herichthys with evaluation of the role of Punta del Morro as a vicariant brake along the Mexican Transition Zone in the context of local and global time frame of cichlid diversification. PeerJ 8:e8818. https://doi.org/10.7717/peerj.8818

    Article  PubMed  PubMed Central  Google Scholar 

  18. Pérez-Miranda F, Mejia O, González-Díaz A, Martínez-Méndez N, Soto-Galera E, Zúñiga G, Říčan O (2020) The role of head-shape ad trophic variation in the diversification of the genus Herichthys in sympatry and allopatry. J Fish Biol 96:1370–1378. https://doi.org/10.1111/jfb.14304

    Article  PubMed  Google Scholar 

  19. Aljanabi SM, Martinez I (1997) Universal and rapid salt-extraction of high quality genomic DNA for PCR-based techniques. Nucl Acids Res 25:4692–4693. https://doi.org/10.1093/nar/25.22.4692

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  20. Caporaso JG, Lauber CL, Walters WA, Berg-Lyons D, Lozupone CA, Turnbaugh PJ et al (2011) Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc Natl Acad Sci 108(Supplement 1):4516–4522. https://doi.org/10.1073/pnas.1000080107

    Article  PubMed  Google Scholar 

  21. Bolyen E, Rideout JR, Dillon MR, Bokulich NA, Abnet CC, Al-Ghalith GA et al (2019) Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat Biotechnol 37:852–857. https://doi.org/10.1038/s41587-019-0209-9

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  22. Andrews S (2010) FastQC: a quality control tool for high throughput sequence data. http://www.bioinformatics.babraham.ac.uk/projects/fastqc/

  23. Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA, Holmes SP (2016) DADA2: high-resolution sample inference from Illumina amplicon data. Nat Methods 13:581–583. https://doi.org/10.1038/nmeth.3869

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  24. Yilmaz P, Parfrey LW, Yarza P, Gerken J, Pruesse E, Quast C et al (2014) The SILVA and “all-species living tree project (LTP)” taxonomic frameworks. Nucleic Acids Res 42(D1):D643–D648. https://doi.org/10.1093/nar/gkt1209

    Article  PubMed  CAS  Google Scholar 

  25. Katoh K, Misawa K, Kuma KI, Miyata T (2002) MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform. Nucleic Acids Res 30:3059–3066. https://doi.org/10.1093/nar/gkf436

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  26. Price MN, Dehal PS, Arkin AP (2010) FastTree 2–approximately maximum-likelihood trees for large alignments. PLoS ONE 5:e9490. https://doi.org/10.1371/journal.pone.0009490

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  27. McMurdie PJ, Holmes S (2013) phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS ONE 8:e61217. https://doi.org/10.1371/journal.pone.0061217

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  28. Dixon P (2003) VEGAN, a package of R functions for community ecology. J Veg Sci 14:927–930. https://doi.org/10.1111/j.1654-1103.2003.tb02228.x

    Article  Google Scholar 

  29. Wickham H (2016) ggplot2: elegant graphics for data analysis. Springer-Verlag, New York

    Book  Google Scholar 

  30. Martinez Arbizu P (2020). pairwiseAdonis: pairwise multilevel comparison using adonis. R package version 0.4

  31. Zhang X, Mallick H, Tang Z, Zhang L, Cui X, Benson AK, Yi N (2017) Negative binomial mixed models for analyzing microbiome count data. BMC Bioinform 18(1):1–10. https://doi.org/10.1186/s12859-016-1441-7

    Article  Google Scholar 

  32. Chiarello M, Auguet JC, Bettarel Y, Bouvier C, Claverie T et al (2018) Skin microbiome of coral reef fish is highly variable and driven by host phylogeny and diet. Microbiome 6:1–14. https://doi.org/10.1186/s40168-018-0530-4

    Article  Google Scholar 

  33. Hutchinson MC, Cagua EF, Balbuena JA, Stouffer DB, Poisot T (2017) paco: implementing procrustean approach to cophylogeny in R. Methods Ecol Evol 8:932–940. https://doi.org/10.1111/2041-210x.12736

    Article  Google Scholar 

  34. De Cock M, Virgilio M, Vandamme P, Augustinos A et al (2019) Impact of sample preservation and manipulation on insect gut microbiome profiling. A test case with fruit flies (Diptera, Tephritidae). Front Microbiol 10:2833. https://doi.org/10.3389/fmicb.2019.02833

    Article  PubMed  PubMed Central  Google Scholar 

  35. Greiman SE, Cook JA, Odem T, Cranmer K et al (2020) Microbiomes from biorepositories? 16S rRNA bacterial amplicon sequencing of archived and contemporary intestinal samples of wild mammals (Eulipotyphla: Soricidae). Front Ecol Evol. https://doi.org/10.3389/fevo.2020.555386

    Article  Google Scholar 

  36. Neu AT, Hughes IV, Allen EE, Roy K (2021) Decade-scale stability and change in a marine bivalve microbiome. Mol Ecol 30(5):1237–1250. https://doi.org/10.1111/mec.15796

    Article  PubMed  CAS  Google Scholar 

  37. Hildonen M, Kodama M, Puetz LC, Gilbert MTP, Limborg MT (2019) A comparison of storage methods for gut microbiome studies in teleosts: insights from rainbow trout (Oncorhynchus mykiss). J Microbiol Methods 160:42–48. https://doi.org/10.1016/j.mimet.2019.03.010

    Article  PubMed  CAS  Google Scholar 

  38. Liu H, Guo X, Gooneratne R, Lai R, Zeng C, Zhan F, Wang W (2016) The gut microbiome and degradation enzyme activity of wild freshwater fishes influenced by their trophic levels. Sci Rep 6:1–12. https://doi.org/10.1038/srep24340

    Article  CAS  Google Scholar 

  39. Li T, Long M, Li H, Gatesoupe FJ, Zhang X, Zhang Q et al (2017) Multi-omics analysis reveals a correlation between the host phylogeny, gut microbiota and metabolite profiles in cyprinid fishes. Front Microbiol 8:454. https://doi.org/10.3389/fmicb.2017.00454

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  40. Debelius J, Song SJ, Vazquez-Baeza Y, Xu ZZ et al (2016) Tiny microbes, enormous impacts: what matters in gut microbiome studies? Genome Biol 17:1–12. https://doi.org/10.1186/s13059-016-1086-x

    Article  Google Scholar 

  41. Smith CC, Snowberg LK, Caporaso JG, Knight R, Bolnick DI (2015) Dietary input of microbes and host genetic variation shape among-population differences in stickleback gut microbiota. ISME J 9:2515–2526. https://doi.org/10.1038/ismej.2015.64

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  42. McCauley M, German DP, Lujan NK, Jackson CR (2020) Gut microbiomes of sympatric Amazonian wood-eating catfishes (Loricariidae) reflect host identity and little role in wood digestion. Ecol Evol 10:7117–7128. https://doi.org/10.1002/ece3.6413

    Article  PubMed  PubMed Central  Google Scholar 

  43. Bledsoe JW, Waldbieser GC, Swanson KS, Peterson BC, Small BC (2018) Comparison of chanel catfish and blue catfish gut microbiota assemblages shows minimal effects of host genetics on microbial structure and inferred function. Front Microbiol 9:1073. https://doi.org/10.3389/fmicb.2018.01073

    Article  PubMed  PubMed Central  Google Scholar 

  44. Sylvain FÉ, Holland A, Bouslama S, Audet-Gilbert É, Lavoie C, Val AL, Derome N (2020) Fish skin and gut microbiomes show contrasting signatures of host species and habitat. Appl Environ Microbiol 86:16. https://doi.org/10.1128/aem.00789-20

    Article  CAS  Google Scholar 

  45. Riiser ES, Haverkamp TH, Varadharajan S, Borgan Ø, Jakobsen KS, Jentoft S, Star B (2020) Metagenomic shotgun analyses reveal complex patterns of intra-and interspecific variation in the intestinal microbiomes of codfishes. Appl Environ Microbiol 86:6. https://doi.org/10.1128/aem.02788-19

    Article  CAS  Google Scholar 

  46. Rennison DJ, Rudman SM, Schluter D (2019) Parallel changes in gut microbiome composition and function during colonization, local adaptation and ecological speciation. Proc R Soc B 286:20191911. https://doi.org/10.1098/rspb.2019.1911

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  47. Youngblut ND, Reischer GH, 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 10:1–15. https://doi.org/10.1038/s41467-019-10191-3

    Article  CAS  Google Scholar 

  48. Franchini P, Fruciano C, Frickey T, Jones JC, Meyer A (2014) The gut microbial community of Midas cichlid fish in repeatedly evolved limnetic-benthic species pairs. PLoS ONE 9:e95027. https://doi.org/10.1371/journal.pone.0095027

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  49. Groussin M, Mazel F, Alm EJ (2020) Co-evolution and co-speciation of host-gut bacteria systems. Cell Host Microbe 28(1):12–22. https://doi.org/10.1016/j.chom.2020.06.013

    Article  PubMed  CAS  Google Scholar 

  50. Matschiner M (2019) Gondwanan vicariance or trans-Atlantic dispersal of cichlid fishes: a review of the molecular evidence. Hydrobiologia 832:9–37. https://doi.org/10.1007/s10750-018-3686-9

    Article  Google Scholar 

Download references

Acknowledgements

Technical assistance is acknowledged to O Gaona (IE, UNAM) and J Ortiz (FC, UNAM). We also like to thank Eduardo Soto Galera for provide access to the museum collections and to four anonymous reviewers for their useful comments that allow to improve the manuscript.

Funding

This study was funded by Instituto de Ecología, UNAM (LIF). ASQ received a graduate studies scholarship from CONACyT. ESGA received a postdoctoral scholarship from DGAPA-UNAM.

Author information

Authors and Affiliations

Authors

Contributions

OM, LIF: Developed the idea. FPM, ESGA: Carried out the molecular work. OM, ASQ, FPM: Carried out the data analyses. OM, LIF, ASQ, FPM, ESGA: Wrote the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Omar Mejía.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical Approval

No approval of research ethics committees was required due that all samples used proceed from museum specimens.

Consent for Publication

Not applicable.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (PDF 894 kb)

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mejía, O., Sánchez-Quinto, A., Gómez-Acata, E.S. et al. “Unraveling the Gut Microbiome of the Genus Herichthys (Pisces: Cichlidae): What Can We Learn from Museum Specimens?”. Curr Microbiol 79, 346 (2022). https://doi.org/10.1007/s00284-022-03047-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s00284-022-03047-5

Navigation