Mu Peng¹ , Syed Sadaqat Shah² , Qiuyu Wang¹ , Fanjuan Meng¹

1 Colleague of Life Science, Northeast Forestry University, Harbin, 150040, China
2 Key Laboratory of Vegetation Ecology, Ministry of Education, Institute of Grassland Science, Northeast Normal University, Changchun 130024, China
Author    Correspondence author
Molecular Microbiology Research, 2017, Vol. 7, No. 2   doi: 10.5376/mmr.2017.07.0002
Received: 26 Jun., 2017    Accepted: 25 Jul., 2017    Published: 02 Aug., 2017

This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Peng M., Shah S.S., Wang Q.Y., and Meng F.J., 2017, Response of soil bacterial community structure to land-use conversion of natural forests in Maoershan National Forest Park, China, Molecular Microbiology Research, 7(2): 10-19 (doi: 10.5376/mmr.2017.07.0002)

To compare and evaluate the soil bacterial community composition in Maoershan National Forest Park, we analyzed soil samples from four replicated land-use types (hardwood forests, cultivated lands, settlement and slash lands) using a denaturing gradient gel electrophoresis (DGGE) method based on 16s rRNA gene fragments. Forty-two DGGE bands were successfully excised for sequencing. Our results revealed that the conversion of natural forest to other land-use types had a significant effect on the soil bacterial community. Bacteroidetes was absent in forest soils. Beta-Proteobacteria was unique to settlement soils, whereas Cyanobacteria and Verrucomicrobia were absent in agricultural soils. Additionally, Acidobacteria and Proteobacteria (α, β, γ, δ classes) were the dominant bacterial communities in all soils. Thus, conversion of the forest land into other land-use types resulted in changes in the bacterial communities which might affect the productivity of the soil ecosystem. Together these results suggested that the utility of using sequence-based approaches to analyze bacterial communities provides detailed information on individual bacterial community composition and permit the robust assessment of the biogeographical patterns.

Bacterial community structure; 16S rRNA; Forest; Conversion of land-use