Microbial Ecology

, Volume 67, Issue 4, pp 919–930 | Cite as

Land Use Type Significantly Affects Microbial Gene Transcription in Soil

  • Heiko Nacke
  • Christiane Fischer
  • Andrea Thürmer
  • Peter Meinicke
  • Rolf Daniel
Soil Microbiology


Soil microorganisms play an essential role in sustaining biogeochemical processes and cycling of nutrients across different land use types. To gain insights into microbial gene transcription in forest and grassland soil, we isolated mRNA from 32 sampling sites. After sequencing of generated complementary DNA (cDNA), a total of 5,824,229 sequences could be further analyzed. We were able to assign nonribosomal cDNA sequences to all three domains of life. A dominance of bacterial sequences, which were affiliated to 25 different phyla, was found. Bacterial groups capable of aromatic compound degradation such as Phenylobacterium and Burkholderia were detected in significantly higher relative abundance in forest soil than in grassland soil. Accordingly, KEGG pathway categories related to degradation of aromatic ring-containing molecules (e.g., benzoate degradation) were identified in high abundance within forest soil-derived metatranscriptomic datasets. The impact of land use type forest on community composition and activity is evidently to a high degree caused by the presence of wood breakdown products. Correspondingly, bacterial groups known to be involved in lignin degradation and containing ligninolytic genes such as Burkholderia, Bradyrhizobium, and Azospirillum exhibited increased transcriptional activity in forest soil. Higher solar radiation in grassland presumably induced increased transcription of photosynthesis-related genes within this land use type. This is in accordance with high abundance of photosynthetic organisms and plant-infecting viruses in grassland.


Forest Soil Soil Microbial Community Grassland Soil High Relative Abundance Pfam Family 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors thank the managers of the three exploratories, Swen Renner, Sonja Gockel, Andreas Hemp, Martin Gorke, and Simone Pfeiffer for their work in maintaining the plot and project infrastructure, and Markus Fischer, the late Elisabeth Kalko, Eduard Linsenmair, Dominik Hessenmöller, Jens Nieschulze, Daniel Prati, Ingo Schöning, François Buscot, Ernst-Detlef Schulze, and Wolfgang W. Weisser for their role in setting up the Biodiversity Exploratories project. The work has been funded by the DFG Priority Program 1374 “Infrastructure-Biodiversity-Exploratories” (DA 374/6-1). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Supplementary material

248_2014_377_MOESM1_ESM.pdf (1.8 mb)
ESM 1 (PDF 1845 kb)


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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Heiko Nacke
    • 1
  • Christiane Fischer
    • 1
    • 3
  • Andrea Thürmer
    • 1
  • Peter Meinicke
    • 2
  • Rolf Daniel
    • 1
  1. 1.Department of Genomic and Applied Microbiology and Göttingen Genomics LaboratoryInstitute of Microbiology and Genetics, Georg-August-University GöttingenGöttingenGermany
  2. 2.Department of BioinformaticsInstitute of Microbiology and Genetics, Georg-August-University GöttingenGöttingenGermany
  3. 3.BiK-F Biodiversität und Klima Forschungszentrum, Biodiversity ExploratoriesSenckenberg Gesellschaft für NaturforschungFrankfurtGermany

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