Microbial Ecology

, Volume 75, Issue 4, pp 830–833 | Cite as

The Impact of the Diurnal Cycle on the Microbial Transcriptome in the Rhizosphere of Barley

  • Divyashri Baraniya
  • Paolo Nannipieri
  • Susanne Kublik
  • Gisle Vestergaard
  • Michael SchloterEmail author
  • Anne Schöler


While root exudation follows diurnal rhythms, little is known about the consequences for the microbiome of the rhizosphere. In this study, we used a metatranscriptomic approach to analyze the active microbial communities, before and after sunrise, in the rhizosphere of barley. We detected increased activities of many prokaryotic microbial taxa and functions at the pre-dawn stage, compared to post-dawn. Actinomycetales, Planctomycetales, Rhizobiales, and Burkholderiales were the most abundant and therefore the most active orders in the barley rhizosphere. The latter two, as well as Xanthomonadales, Sphingomonadales, and Caulobacterales showed a significantly higher abundance in pre-dawn samples compared to post-dawn samples. These changes in taxonomy coincide with functional changes as genes involved in both carbohydrate and amino acid metabolism were more abundant in pre-dawn samples compared to post-dawn samples. This study significantly enhances our present knowledge on how rhizospheric microbiota perceives and responds to changes in the soil during dark and light periods.


Rhizosphere Metatranscriptome Barley Diurnal cycle Microbial dynamics 



We thank Luhua Yang for the advice on germination and planting of the barley seeds and J. BarbroWinkler for technical advice in the greenhouse. We thank European Marie Curie ITN for funding Divyashri Baraniya and Anne Schöler through “TRAINBIODIVERSE” project, grant No. 289949. Gisle Vestergaard is supported by a Humboldt Research Fellowship for postdoctoral researchers.

Compliance with Ethical Standards

Conflict of Interest

The authors declare that they have no conflict of interest.

Ethics Approval

Not applicable

Supplementary material

248_2017_1101_MOESM1_ESM.pdf (362 kb)
ESM 1 Supplementary Fig. 1 (S1): Coverage estimation. The achieved coverage of metatranscriptomic samples was analyzed using Nonpareil and shows similar coverage for all six samples. (PDF 361 kb)
248_2017_1101_MOESM2_ESM.pdf (362 kb)
ESM 2 Supplementary Fig. 2 (S2): The most abundant bacterial orders of significantly different KEGG pathways. Depicted are the ten most abundant bacterial orders in percentages of reads for the pathways, which were more active at pre-dawn (carbohydrate metabolism, nucleotide metabolism, amino acid metabolism and metabolism of cofactors and vitamins). Significant differences between pre-dawn and post-dawn time points were determined by unpaired t-test statistics (∗P < 0.05, n = 3). (PDF 362 kb)
248_2017_1101_MOESM3_ESM.docx (24 kb)
ESM 3 Supplementary Table 1 Pre-processing of Illumina mRNA reads. Supplementary Table 2 Relative abundance of reads belonging to taxonomic classes which were significantly different between day and night. Supplementary Table 3 Relative abundance of reads belonging to KEGG pathways which were significantly different between day and night (DOCX 24 kb)
248_2017_1101_MOESM4_ESM.docx (30 kb)
ESM 4 Supplementary Methods (DOCX 30 kb)


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Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  • Divyashri Baraniya
    • 1
  • Paolo Nannipieri
    • 1
  • Susanne Kublik
    • 2
  • Gisle Vestergaard
    • 2
  • Michael Schloter
    • 2
    Email author
  • Anne Schöler
    • 2
  1. 1.Department of Agrifood Production and Environmental SciencesUniversity of FlorenceFlorenceItaly
  2. 2.Research Unit for Comparative Microbiome AnalysisHelmholtz Zentrum MünchenNeuherbergGermany

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