Analysis of peat bacterial diversity in oil palm plantations and a logged forest in Jambi, Indonesia, using PCR-DGGE technique

Abstract

Jambi Province has around 617,000 hectares of peatlands spread across six districts, including Tanjung Jabung Timur. Reports on microbial diversity under different land cover, especially those using molecular techniques, were very limited. The study aimed to evaluate the impact of peatlands conversion on soil bacterial biodiversity, through the analysis of 16S-rDNA gene employing polymerase chain reaction combined with denaturing gradient gel electrophoresis (PCR-DGGE). Peat soil samples were taken from the topsoil (rhizosphere) of 3 sites, i.e. (A) conventional drained (50 to 70 cm) oil palm plantation, (B) shallow drained (30 to 50 cm) oil palm plantation, and (C) logged-over peat forest. Sequential analysis based on the 16S rRNA gene showed that 15 operational taxonomic units (OTUs) could be grouped into 3 phyla, namely Proteobacteria, Acidobacteria, and Actinobacteria. The alignment result of nucleotide shows that 4 of 15 bands of DGGE were identified as the uncultured bacterium (Sulfurospirillum, Acidobacteria, Rhodoplane, and Magnetospirillum). Overall, the Shannon-Weaver biodiversity index showed that the conversion of peatlands to oil palm plantation increased bacterial biodiversity. This could be attributed to drainage, ferlilization, and biomass inputs under the oil palm plantations. The higher biodiversity under oil palm plantations also implies a higher rate of peat decomposition under this land use, relative to the forest.

Bacteria and Soil Enzymes Supporting the Valorization of Forested Soils

“…In turn, Liu et al [85] found that the soils of the deciduous and coniferous forests and meadows of the Songshan forest reserve in Yanqing (Beijing, China) were most abundant in the DA101 genus bacteria. Analyzing the results cited in the above literature [30,74,[81][82][83][84] and the results of our study, it can be concluded that although the composition of bacterial communities in soils and their diversity vary, certain bacterial genera occur in most forest ecosystems, while others constitute the core microbiome of individual habitats. Thus, we have shown that the genus Bacillus is most characteristic for the spruce stand; Sphingomonas and Iamia, for the larch stand; and Burkholderia, for the birch stand.…”

“…The bacteria of the genus Rhodoplanes and Burkholderia also dominated the bacterial community in the pine forest soils of the Manowo Forest District in northern Poland [81] and in the humid tropical forests of Costa Rica [82]. The genus Rhodoplanes was additionally found to prevail in the soils of the cleared forest in Indonesia [83] and, in our earlier research, in the forests of north-eastern Poland [57]. Moreover, Eaton et al [82] have drawn attention to the bacteria of the Solibacter, Comomonas, Azospirillum, Geobacter, and Bradyrhizobium genera, whereas Lasota e al.…”

Unraveling Techniques for Plant Microbiome Structure Analysis

“…Detection of point mutations in DNA sequences could be achieved by these methods. Reliability, reproducibility to some extent and by some means inexpensive was the advantage of these methods which could provide simultaneous analysis of various samples; and present the fluctuations in microbial populations [59,60].…”

Ecological Response in the Integrated Process of Biostimulation and Bioaugmentation of Diesel-Contaminated Soil

“…With the rapid development of biotechnology methods and molecular technology, 16S rRNA gene library, denaturing gradient gel electrophoresis (DGGE) (The abbreviated terms mentioned in the article are presented in Table A1 (Appendix A)), single-strand conformation polymorphism (SSCP), DNA hybridization such as fluorescence in situ hybridization (FISH) and DNA microarray are widely used in the evaluation of different bioremediation protocols [39]. For polycyclic aromatic hydrocarbons (PAHs) and total petroleum hydrocarbon (TPH) bioremediation process, polymerase chain reaction (PCR) [40], PCR-DGGE [41], and high-throughput sequencing [42] are widely used. Illumina's MiSeq sequencing technology is a low-throughput, fast, and high-accuracy platform that is becoming the leading analysis technology in the market.…”