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Form, function and physics: The ecology of biogenic stabilization
Published in Silke Wieprecht, Stefan Haun, Karolin Weber, Markus Noack, Kristina Terheiden, River Sedimentation, 2016
D.M. Paterson, J.M. Kenworthy, J.A. Hope
The next phase of research is likely to rely on advances in molecular analysis, metagenomics (Thomas et al., 2012) and metabolomics (Nicholson & Lindon, 2006). Prokaryotes (both archaebacteria and eubacteria) have largely been treated as a “black box” since only about 2% of known bacteria can be cultured (Wade, 2002). Now metagenomic analysis of environmental DNA creates a database of operational taxonomic units (OTU, a molecular analog for species) that reveals the diversity of entire microbial assemblages in immense detail. In our own recent work, we have recorded nearly 200,000 bacterial OTUs from a laboratory incubation experiment using natural sediments (Hicks et al., submitted). Having to interpret this level of microbial biodiversity will become common in the next decade but in itself will be of less interest than the study of the processes (metabolomics) that the bacterial assemblages drive. Part of this research should be the analysis of polymer production and secretion into the environment, the medium that is probably the major factor in mediating the response of the sediment to environmental forcing. Knowledge of how bacterial metabolism changes in response to environmental challenge will become a driving force for environmental microbial ecology (Logue et al., 2015).
Impact of long-term cultivation with crude oil on wetland microbial community shifts and the hydrocarbon degradation potential
Published in Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 2021
Haijun Liu, Guo Yang, Hui Jia, Jun Yao
The water phase of the culture was separated with a separating funnel. For each sample, 80 mL of enriched culture was used to collect bacteria on a 0.22 μm poly-carbonate membrane filter for profiling the bacterial communities. Biological samples were sealed in sterile centrifuge tubes and transported to the company (Majorbio, Beijing) on dry ice for Illumina high-throughput sequencing analysis. The V3-V4 hypervariable region of the bacterial 16S rRNA gene was amplified using the primer pair 338 F (5ʹ-ACTCCTACGGGAGGCAGCAG-3ʹ) and 806 R (5ʹ-GGACTACHVGGGTWTCTAAT-3ʹ) (Xu et al. 2016). The quality control processing of raw sequence data was performed before the biodiversity analysis. Reads were demultiplexed and quality-filtered using QIIME version 1.9.1, and chimeric sequences were identified and removed using UCHIME (Song et al. 2017). All samples were normalized to 26,874 16S rRNA gene sequences per sample. Subsequently, good quality sequences were utilized to determine the operational taxonomic units (OTUs) at 97% similarity. Rarefaction curves were generated to assess the sampling efficiency. The microbial taxonomic classification was processed using the RDP classifier based on the SILVA database for bacterial communities. The α-diversity indices were calculated to explore the bacterial diversity, and a heatmap analysis was also used to profile the top 30 genera in each sample.
Characterization and application of an anaerobic, iron and sulfate reducing bacterial culture in enhanced bioremediation of acid mine drainage impacted soil
Published in Journal of Environmental Science and Health, Part A, 2020
Microbial communities were analyzed with respect to the major Operational Taxonomic Units (OTUs). OTU level data indicated that the members of the bioaugmented consortium contributed substantially in BABS community (Figures B3 and B4). The topmost abundant OTUs (top 25; 82% abundance) of the consortium were detected in BA community as a minor fraction (0.4%), whereas the same OTUs represented 37% in BABS community (Figure B3). These results indicated that while the major OTUs (species) of the consortium were able to survive in BA that was devoid of any carbon source, got enriched considerably in BABS that received organic carbon supplementation, thus confirming the role of available organic carbon on the proliferation of desired organisms. Interestingly, out of the top 25 OTUs of BABS community, only seven belonged to the consortium (covering 35% of BABS), and the rest were indigenous to the AIS (Figure B4). This result confirmed that the addition of organic carbon not only promoted the growth of members from the consortium but also enhanced the indigenous Fe3+/SO42− reducing populations of AIS. The PCA based analysis showed that AC and BA, as well as BABS and BS, were closely associated with each other due to their similarity in microbial community composition (Figure B5). The PCA based analysis confirmed the substantial shift in microbial community composition of AIS upon treatments.
Control of H2S generation in simultaneous removal of NO and SO2 by rotating drum biofilter coupled with FeII(EDTA)
Published in Environmental Technology, 2018
Jun Chen, Bingbin Li, Ji Zheng, Jianmeng Chen
Genomic DNA was extracted from the cells according to the instruction of the DNA isolation kit obtained from Shanghai Biotechnology Co., Ltd. Purified DNA was used as a template for PCR amplification with high-fidelity DNA polymerase. The 16S rRNA genes were amplified using the universal primers 341F: 3′-CCCTACACGACGCTCTCCGATCTGCCTACGGGNGGCWGCAG-5′ and 805R: 3′-GACTGGAGTTCCTTGGCACCCGAGAATTCCAGACTACHVGGGTATCTAA TCC-5′. Both primers were modified to contain an Illumina adapter region (bold), and the forward primer was encoded with a 12 bp barcode for multiplex sequencing. The thermal PCR conditions were as follows: initial denaturation at 94°C for 5 min and 30 cycles of denaturation at 94°C for 1 min, annealing at 54°C for 1 min, and an extension at 72°C for 3 min, followed by a final extension at 72°C for 10 min. After amplification, PCR products were analyzed through agarose gel electrophoresis. The obtained data were optimized by removing low-quality sequences, unrecognized reverse primers, and any ambiguous base calls, with a length <200 bp. High-quality sequences were clustered into 97% similarity operational taxonomic units (OTUs) using UCLUST software. A representative sequence from each OTU was classified and phylogenetically assigned to a taxonomic identity (phylum and genus levels) using RDP classifier. Shannon diversity indices and species richness estimators were generated for each sample using Quantitative Insights Into Microbial Ecology (QIIME) pipeline version 1.3.0. (http://qiime.org) [26].