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Diversity of microbiota associated with symptomatic and non-symptomatic bacterial wilt-diseased banana plants determined using 16S rRNA metagenome sequencing

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Abstract

Banana is one of the most important fruits cultivated in Malaysia, and it provides many health benefits. However, bacterial wilt disease, which attacks bananas, inflicts major losses on the banana industry in Malaysia. To understand the complex interactions of the microbiota of bacterial wilt-diseased banana plants, we first determined the bacterial communities residing in the pseudostems of infected (symptomatic) and diseased-free (non-symptomatic) banana plants. We characterized the associated microorganisms using the targeted 16S rRNA metagenomics sequencing on the Illumina MiSeq platform. Taxonomic classifications revealed 17 and nine known bacterial phyla in the tissues of non-symptomatic and symptomatic plants, respectively. Cyanobacteria and Proteobacteria (accounted for more than 99% of the 16S rRNA gene fragments) were the two most abundant phyla in both plants. The five major genera found in both plant samples were Ralstonia, Sphingomonas, Methylobacterium, Flavobacterium, and Pseudomonas. Ralstonia was more abundant in symptomatic plant (59% out of the entire genera) as compared to those in the non-symptomatic plant (only 36%). Our data revealed that 102 bacterial genera were only assigned to the non-symptomatic plant. Overall, this study indicated that more diverse and abundant microbiota were associated with the non-symptomatic bacterial wilt-diseased banana plant as compared to the symptomatic plant. The higher diversity of endophytic microbiota in the non-symptomatic banana plant could be an indication of pathogen suppression which delayed or prevented the disease expression. This comparative study of the microbiota in the two plant conditions might provide caveats for potential biological control strategies.

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Acknowledgements

We thank University of Malaya for facilities and support. This project was supported by Postgraduate Research Fund, University of Malaya (No. PV123-2012A awarded to NSMS) and High Impact Research Grants, Ministry of Higher Education (MOHE), Malaysia (No. UM.C/625/1HIR/MOHE/-02 awarded to TKL and H-50001-A000027 awarded to CKG). The first author was financially supported by MOHE, Malaysia and SLAI Scheme, University of Malaya. We would like to acknowledge officers and field-workers from Crop Protection and Plant Quarantine Unit, Department of Agriculture, also the banana smallholder in Negeri Sembilan, Malaysia for giving permission to conduct the sampling of plant materials and assistance in sampling processes.

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Authors and Affiliations

  1. Microbiology Unit, Institute of Biological Sciences, University of Malaya, 50603, Kuala Lumpur, Malaysia

    Nurul Shamsinah Mohd Suhaimi, Noni Ajam, Rofina Yasmin Othman & Kwai Lin Thong

  2. Genetics and Molecular Biology Unit, Institute of Biological Sciences, Faculty of Science, University of Malaya, 50603, Kuala Lumpur, Malaysia

    Share-Yuan Goh & Kok-Gan Chan

  3. Centre for Research in Biotechnology for Agriculture (CEBAR), Research Management and Innovation Complex, University of Malaya, 50603, Kuala Lumpur, Malaysia

    Rofina Yasmin Othman

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  1. Nurul Shamsinah Mohd Suhaimi
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Correspondence to Kwai Lin Thong.

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Electronic supplementary material

Below is the link to the electronic supplementary material.

11274_2017_2336_MOESM1_ESM.pdf

Online Resource 1—Cladogram of bacteria associated with Non-Symptomatic (NS) and Symptomatic (SP) plants tissue samples at the Phylum level. (PDF 85 KB)

11274_2017_2336_MOESM2_ESM.pdf

Online Resource 2—Cladogram of bacteria associated with Non-Symptomatic (NS) and Symptomatic (SP) plants tissue samples at the Order level. (PDF 146 KB)

11274_2017_2336_MOESM3_ESM.pdf

Online Resource 3—Cladogram of bacteria associated with Non-Symptomatic (NS) and Symptomatic (SP) tissue samples at the Genus level. (PDF 238 KB)

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Suhaimi, N.S.M., Goh, SY., Ajam, N. et al. Diversity of microbiota associated with symptomatic and non-symptomatic bacterial wilt-diseased banana plants determined using 16S rRNA metagenome sequencing. World J Microbiol Biotechnol 33, 168 (2017). https://doi.org/10.1007/s11274-017-2336-0

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