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The functional gene composition and metabolic potential of coral-associated microbial communities
Zhang, Y.; Ling, J.; Yang, Q.; Wen, C.; Yan, Q.; Sun, H.; Van Nostrand, J.D.; Shi, Z.; Zhou, J.; Dong, J. (2015). The functional gene composition and metabolic potential of coral-associated microbial communities. NPG Scientific Reports 5(16191): 11 pp. http://dx.doi.org/10.1038/srep16191
In: Scientific Reports (Nature Publishing Group). Nature Publishing Group: London. ISSN 2045-2322; e-ISSN 2045-2322, more
Peer reviewed article  

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Keyword
    Marine/Coastal

Authors  Top 
  • Zhang, Y.
  • Ling, J.
  • Yang, Q.
  • Wen, C.
  • Yan, Q.
  • Sun, H.
  • Van Nostrand, J.D.
  • Shi, Z.
  • Zhou, J.
  • Dong, J.

Abstract
    The phylogenetic diversity of coral-associated microbes has been extensively examined, but some contention remains regarding whether coral-associated microbial communities are species-specific or site-specific. It is suggested that corals may associate with microbes in terms of function, although little is known about the differences in coral-associated microbial functional gene composition and metabolic potential among coral species. Here, 16S rRNA Illumina sequencing and functional gene array (GeoChip 5.0) were used to assess coral-associated microbial communities. Our results indicate that both host species and environmental variables significantly correlate with shifts in the microbial community structure and functional potential. Functional genes related to key biogeochemical cycles including carbon, nitrogen, sulfur and phosphorus cycling, metal homeostasis, organic remediation, antibiotic resistance and secondary metabolism were shown to significantly vary between and among the four study corals (Galaxea astreata, Porites lutea, Porites andrewsi and Pavona decussata). Genes specific for anammox were also detected for the first time in the coral holobiont and positively correlated with ammonium. This study reveals that variability in the functional potential of coral-associated microbial communities is largely driven by changes in environmental factors and further demonstrates the importance of linking environmental parameters with genomic data in complex environmental systems.

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