Bioinformatic approaches for analysis of coral-associated bacteria using R programming language
Keywords:16S rRNA, Acropora tenuis, bioinformatics, coral-associated bacteria, R programming language
Recent advances in metagenomics and bioinformatics allow the robust analysis of the composition and abundance of microbial communities, functional genes, and their metabolic pathways. So far, there has been a variety of computational/statistical tools or software for analyzing microbiome, the common problems that occurred in its implementation are, however, the lack of synchronization and compatibility of output/input data formats between such software. To overcome these challenges, in this study context, we aim to apply the DADA2 pipeline (written in R programming language) instead of using a set of different bioinformatics tools to create our own workflow for microbial community analysis in a continuous and synchronous manner. For the first effort, we tried to investigate the composition and abundance of coral-associated bacteria using their 16S rRNA gene amplicon sequences. The workflow or framework includes the following steps: data processing, sequence clustering, taxonomic assignment, and data visualization. Moreover, we also like to catch readers’ attention to the information about bacterial communities living in the ocean as most marine microorganisms are unculturable, especially residing in coral reefs, namely, bacteria are associated with the coral Acropora tenuis in this case. The outcomes obtained in this study suggest that the DADA2 pipeline written in R programming language is one of the potential bioinformatics approaches in the context of microbiome analysis other than using various software. Besides, our modifications for the workflow execution help researchers to illustrate metagenomic data more easily and systematically, elucidate the composition, abundance, diversity, and relationship between microorganism communities as well as to develop other bioinformatic tools more effectively.
Balser, T. C., McMahon, K. D., Bart, D., Bronson, D., Coyle, D. R., Craig, N., Flores-Mangual, M. L., Forshay, K., Jones, S. E., Kent, A. E., & Shade, A. L. (2006). Bridging the gap between micro - and macro-scale perspectives on the role of microbial communities in global change ecology. Plant and Soil, 289(1), 59–70. https://doi.org/10.1007/s11104-006-9104-5
Bourne, D. G., & Munn, C. B. (2005). Diversity of bacteria associated with the coral Pocillopora damicornis from the Great Barrier Reef. Environmental Microbiology, 7(8), 1162–1174. https://doi.org/10.1111/j.1462-2920.2005.00793.x
Breitbart, M., Salamon, P., Andresen, B., Mahaffy, J. M., Segall, A. M., Mead, D., Azam, F., & Rohwer, F. (2002). Genomic analysis of uncultured marine viral communities. Proceedings of the National Academy of Sciences, 99(22), 14250 LP – 14255. https://doi.org/10.1073/pnas.202488399
Callahan, B. J., McMurdie, P. J., Rosen, M. J., Han, A. W., Johnson, A. J. A., & Holmes, S. P. (2016). DADA2: High-resolution sample inference from Illumina amplicon data. Nature Methods, 13(7), 581–583. https://doi.org/10.1038/nmeth.3869
Kvennefors, E. C. E., Sampayo, E., Kerr, C., Vieira, G., Roff, G., & Barnes, A. C. (2012). Regulation of bacterial communities through antimicrobial activity by the coral holobiont. Microbial Ecology, 63(3), 605–618. https://doi.org/10.1007/s00248-011-9946-0
Langille, M. G. I., Zaneveld, J., Caporaso, J. G., McDonald, D., Knights, D., Reyes, J. A., Clemente, J. C., Burkepile, D. E., Vega Thurber, R. L., Knight, R., Beiko, R. G., & Huttenhower, C. (2013). Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nature Biotechnology, 31(9), 814–821. https://doi.org/10.1038/nbt.2676
Reshef, L., Koren, O., Loya, Y., Zilber-Rosenberg, I., & Rosenberg, E. (2006). The coral probiotic hypothesis. Environmental Microbiology, 8(12), 2068–2073. https://doi.org/10.1111/j.1462-2920.2006.01148.x
Rosenberg, E., Kellogg, C. A., & Rohwer, F. (2007). Coral Microbiology. A Sea of Microbe, 20, 146–154.
Thomas, T., Gilbert, J., & Meyer, F. (2012). Metagenomics - a guide from sampling to data analysis. Microbial Informatics and Experimentation, 2(1), 3. https://doi.org/10.1186/2042-5783-2-3
Wade, W. (2002). Unculturable bacteria--the uncharacterized organisms that cause oral infections. Journal of the Royal Society of Medicine, 95(2), 81–83. https://doi.org/10.1258/jrsm.95.2.81