A metagenomics investigation of carbohydrate-active enzymes along the goat and camel intestinal tract

  • Saad Al-Masaudi
  • Abdessamad El Kaoutari
  • Elodie Drula
  • Elrashdy M. Redwan
  • Vincent Lombard
  • Bernard HenrissatEmail author
Original Paper


Studies of the digestive microbiota of ruminant animals most often focus on the bacterial diversity in the rumen or the feces of the animals, but little is known about the diversity and functions of their distal intestine. Here, the bacterial microbiota of the distal intestinal tract of two goats and two camels was investigated by metagenomics techniques. The bacterial taxonomic diversity and carbohydrate-active enzyme profile were estimated for samples taken from the small intestine, the large intestine, and the rectum of each animal. The bacterial diversity and abundance in the small intestine were lower than in the rectal and large intestinal samples. Analysis of the carbohydrate-active enzyme profiles at each site revealed a comparatively low abundance of enzymes targeting xylan and cellulose in all animals examined, similar to what has been reported earlier for sheep and therefore suggesting that plant cell wall digestion probably takes place elsewhere, such as in the rumen.


Ruminant animals Intestine Microbial diversity Carbohydrate-active enzymes 


Funding information

This project was funded by the Deanship of Scientific Research at King Abdulaziz University, Jeddah, under grant no. 67/130/35-HiCi.

Compliance with ethical standards

The Ethics Committee of King Abdulaziz University for Experimental Animals and Humans has given its consent to conduct our experiments. The animal samples were taken from the Jeddah Municipality Slaughterhouses, which deploy well-qualified veterinarians who supervised our sample isolation.

Competing interests

The authors declare that they have no conflict of interest.

Supplementary material

10123_2019_68_MOESM1_ESM.docx (13 kb)
ESM 1 (DOCX 12 kb)
10123_2019_68_MOESM2_ESM.docx (76 kb)
ESM 2 (DOCX 75 kb)


  1. Al-Masaudi S, El Kaoutari A, Drula E, Al-Mehdar H, Redwan EM, Lombard V, Henrissat B (2017) A metagenomics investigation of carbohydrate-active enzymes along the gastrointestinal tract of Saudi sheep. Front Microbiol 8(666).
  2. Cantarel BL, Coutinho PM, Rancurel C, Bernard T, Lombard V, Henrissat B (2009) The Carbohydrate-Active EnZymes database (CAZy): an expert resource for glycogenomics. Nucleic Acids Res 37:D233–D238. CrossRefGoogle Scholar
  3. Cantarel BL, Lombard V, Henrissat B (2012) Complex carbohydrate utilization by the healthy human microbiome. PLoS One 7(6):e28742. CrossRefGoogle Scholar
  4. 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, Zaneveld J, Knight R (2010) QIIME allows analysis of high-throughput community sequencing data. Nat Methods 7(5):335–336. CrossRefGoogle Scholar
  5. Cersosimo LM, Lachance H, St-Pierre B, van Hoven W, Wright AD (2015) Examination of the rumen bacteria and methanogenic archaea of wild impalas (Aepyceros melampus melampus) from Pongola, South Africa. Microb Ecol 69:577–585. CrossRefGoogle Scholar
  6. Crespo-Piazuelo D, Estellé J, Revilla M, Criado-Mesas L, Ramayo-Caldas Y, Óvilo C, Fernández AI, Ballester M, Folch JM (2018) Characterization of bacterial microbiota compositions along the intestinal tract in pigs and their interactions and functions. Sci Rep 8(1):12727. CrossRefGoogle Scholar
  7. Edgar RC (2017) UNBIAS: an attempt to correct abundance bias in 16S sequencing, with limited success. BioRXiv.
  8. El Kaoutari A, Armougom F, Gordon JI, Raoult D, Henrissat B (2013) The abundance and variety of carbohydrate-active enzymes in the human gut microbiota. Nat Rev Microbiol 11:497–504. CrossRefGoogle Scholar
  9. Ericsson AC, Johnson PJ, Lopes MA, Perry SC, Lanter HR (2016) A microbiological map of the healthy equine gastrointestinal tract. PLoS One 11(11):e0166523. CrossRefGoogle Scholar
  10. Grabherr MG, Haas BJ, Yassour M, Levin JZ, Thompson DA, Amit I, Adiconis X, Fan L, Raychowdhury R, Zeng Q, Chen Z, Mauceli E, Hacohen N, Gnirke A, Rhind N, di Palma F, Birren BW, Nusbaum C, Lindblad-Toh K, Friedman N, Regev A (2011) Full-length transcriptome assembly from RNA-Seq data without a reference genome. Nat Biotechnol 29(7):644–652. CrossRefGoogle Scholar
  11. Gruninger RJ, Sensen CW, McAllister TA, Forster RJ (2014) Diversity of rumen bacteria in Canadian cervids. PLoS One 9(2):e89682. CrossRefGoogle Scholar
  12. Hess M, Sczyrba A, Egan R, Kim TW, Chokhawala H, Schroth G, Luo S, Clark DS, Chen F, Zhang T, Mackie RI, Pennacchio LA, Tringe SG, Visel A, Woyke T, Wang Z, Rubin EM (2011) Metagenomic discovery of biomass-degrading genes and genomes from cow rumen. Science 331:463–467. CrossRefGoogle Scholar
  13. Lombard V, Golaconda Ramulu H, Drula E, Coutinho PM, Henrissat B (2014) The carbohydrate-active enzymes database (CAZy) in 2013. Nucleic Acids Res 42:D490–D495. CrossRefGoogle Scholar
  14. Mailhe M, Ricaboni D, Vitton V, Gonzalez JM, Bachar D, Dubourg G, Cadoret F, Robert C, Delerce J, Levasseur A, Fournier PE, Angelakis E, Lagier JC, Raoult D (2018) Repertoire of the gut microbiota from stomach to colon using culturomics and next-generation sequencing. BMC Microbiol 18(1):157. CrossRefGoogle Scholar
  15. Ming L, Yi L, Siriguleng HS, He J, Hai L, Wang Z, Guo F, Qiao X, Jirimutu (2017) Comparative analysis of fecal microbial communities in cattle and Bactrian camels. PLoS One 12(3):e0173062. CrossRefGoogle Scholar
  16. Muegge BD, Kuczynski J, Knights D, Clemente JC, González A, Fontana L, Henrissat B, Knight R, Gordon JI (2011) Diet drives convergence in gut microbiome functions across mammalian phylogeny and within humans. Science 332:970–974. CrossRefGoogle Scholar
  17. Nathani NM, Patel AK, Mootapally CS, Reddy B, Shah SV, Lunagaria PM, Kothari RK, Joshi CG (2015) Effect of roughage on rumen microbiota composition in the efficient feed converter and sturdy Indian Jaffrabadi buffalo (Bubalus bubalis). BMC Genomics 16:1116. CrossRefGoogle Scholar
  18. Omoniyi LA, Jewell KA, Isah OA, Neumann AP, Onwuka CF, Onagbesan OM, Suen G (2014) An analysis of the ruminal bacterial microbiota in West African Dwarf sheep fed grass- and tree-based diets. J Appl Microbiol 116:1094–1105. CrossRefGoogle Scholar
  19. Pearson WR, Wood T, Zhang Z, Miller W (1997) Comparison of DNA sequences with protein sequences. Genomics 46:24–36CrossRefGoogle Scholar
  20. Pitta DW, Indugu N, Kumar S, Vecchiarelli B, Sinha R, Baker LD, Bhukya B, Ferguson JD (2016) Metagenomic assessment of the functional potential of the rumen microbiome in Holstein dairy cows. Anaerobe 38:50–60. CrossRefGoogle Scholar
  21. Pope PB, Mackenzie AK, Gregor I, Smith W, Sundset MA, McHardy AC, Morrison M, Eijsink VG (2012) Metagenomics of the Svalbard reindeer rumen microbiome reveals abundance of polysaccharide utilization loci. PLoS One 7(6):e38571. CrossRefGoogle Scholar
  22. Salgado-Flores A, Bockwoldt M, Hagen LH, Pope PB, Sundset MA (2016) First insight into the faecal microbiota of the high Arctic muskoxen (Ovibos moschatus). Microb Genom 2(7):e000066. Google Scholar
  23. Schloss PD, Westcott SL, Ryabin T, Hall JR, Hartmann M, Hollister EB, Lesniewski RA, Oakley BB, Parks DH, Robinson CJ, Sahl JW, Stres B, Thallinger GG, Van Horn DJ, Weber CF (2009) Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl Environ Microbiol 75(23):7537–7541. CrossRefGoogle Scholar
  24. Xue M, Wu L, He Y, Liang H, Wen C (2018) Biases during DNA extraction affect characterization of the microbiota associated with larvae of the Pacific white shrimp, Litopenaeus vannamei. Peer J 6:e5257. CrossRefGoogle Scholar
  25. 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. CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Biological SciencesKing Abdulaziz UniversityJeddahSaudi Arabia
  2. 2.Marseille Cancer Research Center, Institut Paoli-Calmettes, INSERM, CNRSAix-Marseille UniversityMarseilleFrance
  3. 3.CNRS UMR 7257, Aix-Marseille UniversityMarseilleFrance
  4. 4.INRA, USC 1408 AFMBMarseilleFrance

Personalised recommendations