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Microbiome and Metagenomics Researches in Nigeria
Published in Nwadiuto (Diuto) Esiobu, James Chukwuma Ogbonna, Charles Oluwaseun Adetunji, Olawole O. Obembe, Ifeoma Maureen Ezeonu, Abdulrazak B. Ibrahim, Benjamin Ewa Ubi, Microbiomes and Emerging Applications, 2022
Francisca O. Nwaokorie, Ime R. Udotong, Nwadiuto (Diuto) Esiobu, Ifeoma Enweani-Nwokelo
Metagenomic analysis was first carried out using Roche/454 platform. Bioinformatics information following sequencing was provided on BLAST hit, Internal Label, frequency of BLAST hit in the samples as well as count reads corresponding to the BLAST hit. From 2015, similar Nigerian samples were analysed following the introduction of Illumina MiSeq Platform. This technique was used in the analysis of microbial diversity of a remote aviation fuel contaminated sediment of a lentic ecosystem in Ibeno, Nigeria (Udotong et al., 2015). Many other studies followed in that line, and commercialized metagenomic services were obtained from different countries abroad to study soil samples, sediments, shipwrecks, anaerobic digesters, animals (chicken dungs), fruits and human faeces, and oral and vaginal microbiomes. Bioinformatic analysis thereafter expanded to the use of more platforms like Quantitative Insight into Microbial Ecology (QIIME) (Kuczynski et al., 2012) and Kyoto Encyclopedia of Genes and Genomes (KEGG) (Kanehisa and Goto, 2000).
Microbial Reservoir Souring
Published in Kenneth Wunch, Marko Stipaničev, Max Frenzel, Microbial Bioinformatics in the Oil and Gas Industry, 2021
Matthew Streets, Leanne Walker
The 16S rRNA metagenomic analysis technique involves DNA amplification via targeting 16S rRNA gene sequences with universal primers to isolate bacterial and archaeal DNA within the sample. The amplified sequences are then processed through an analytical pipeline (commonly Quantitative Insights Into Microbial Ecology, or ‘QIIME’) and are clustered into operational taxonomic units (OTUs) for further processing and sequence analysis. The end product of this analytical method is that all prokaryotic 16S rRNA gene sequences within the samples can be identified and compared against gene libraries, resulting in the identification and estimated abundance of specific prokaryotic classes, families, and genera (Klindworth et al. 2013, Bonifay et al. 2017).
Effect of humic acid on microbial arsenic reduction in anoxic paddy soil
Published in Yong-Guan Zhu, Huaming Guo, Prosun Bhattacharya, Jochen Bundschuh, Arslan Ahmad, Ravi Naidu, Environmental Arsenic in a Changing World, 2019
Total RNA was extracted using a MoBio PowerSoilTM Total RNA Isolation Kit (Mio Bio Laboratories, USA). The RNA was reverse transcribed using a PrimeScript RT reagent kit with gDNA Eraser (Takara, Shiga, Japan). The cDNA samples were amplified with primers specific to V4 region of 16S rRNA gene using primers 515F and 806R for further high-throughput sequencing. Data from 16S rRNA amplicon libraries were processed using the Quantitative Insights Into Microbial Ecology (QIIME 1.8.0) toolkit.
Shift of microbial diversity and function in high-efficiency performance biotrickling filter for gaseous xylene treatment
Published in Journal of the Air & Waste Management Association, 2019
Mingxue Li, Yantao Shi, Yixuan Li, Yizhe Sun, Chunhui Song, Zhiyong Huang, Zongzheng Yang, Yifan Han
When the xylene removal efficiency in the deep acclimation phase was stable, the upper (10 cm from the surface), middle, and lower (10 cm from the bottom) packings in the biotrickling filter were collected. Cells attached to the packings were washed with sterilized 0.85% NaCl solution and centrifuged at 10,000 × g for 1 min. The precipitate was retained for total DNA extraction using the DNeasy PowerSoil Kit (Qiagen, Hilden, Germany) following the procedure in the product manual. Three replicate samples for each layer were extracted and numbered t1, t2, t3, m1, m2, m3, b1, b2, and b3, respectively. Spectrophotometry (Thermo Scientific NanoDrop 2000C, Thermo Fisher Scientific Inc, Massachusetts, USA) and agarose gel electrophoresis were used to determine the quality of the DNA. High-throughput sequencing was conducted using the Illumina MiSeq 2500 platform at Novogene (Beijing, China). The V4 region of the 16S rRNA gene was amplified in each DNA sample. The sequencing results were analyzed using the Quantitative Insights Into Microbial Ecology (QIIME) software (Caporaso et al. 2010).
Assays and enumeration of bioaerosols-traditional approaches to modern practices
Published in Aerosol Science and Technology, 2020
Maria D. King, Ronald E. Lacey, Hyoungmook Pak, Andrew Fearing, Gabriela Ramos, Tatiana Baig, Brooke Smith, Alexandra Koustova
Another software called the Quantitative Insights Into Microbial Ecology (QIIME) and QIIME2 can be used for sequencing 16S rRNA gene fragments and identifying their taxonomy classification (Lawley and Tannock 2016; Hall and Beiko 2018). However, it has been reported that amplicons from Illumina sequencing sometimes contain errors in quality filtering and constructing OTUs for clusters of sequencing reads that differ by less than a fixed dissimilarity threshold. This problem can be overcome by using another open-source R package called DADA2, which contains an algorithm that can correct these errors enabling amplicon sequence variants (ASVs) to be resolved to the level of single-nucleotide differences over the sequenced gene region (Callahan et al. 2016). Recent debates focus on phasing out the traditional OTUs of marker gene sequences and instead delineating microbial taxa using exact sequence variants (ESVs) (Callahan, McMurdie, and Holmes 2017; Glassman and Martiny 2018). This approach avoids clustering sequences and instead uses only unique, identical 16S rRNA sequences for downstream community analyses that could differ by only one base pair. Another error-prone process is the conversion of genome abundances to cell numbers that requires taxa-specific information about the number of genome copies in the cell (Bonk et al. 2018). However, this is a useful way to normalize NGS data (Dannemiller et al. 2014). A number of additional tools are available to ‘de-noise’ and identify ESVs including Deblur, oligotyping, and UNOISE2 (Amir et al. 2017). Recent studies have found that archaea and bacteria can have less or more than 10 genome copies per cell, making it hard to correct for ploidy (Soppa 2014).
Suitability of wetland microbial consortium for enhanced and sustained power generation from distillery effluent in microbial fuel cell
Published in Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 2020
Aradhana Singh, Anubha Kaushik
After completion of 3 semi-fed batch cycles of 10 days each, the biofilm developed on the anodic electrode of MFC, that showed best power generation was harvested. DNA was isolated from the biofilm generated on the graphite electrode surface using Qiagen Soil gDNA kit. The amplicon library was prepared using Nextera XT Index Kit (Illumina Inc.) as per the 16S Metagenomic Sequencing Library preparation protocol. Primers used in the study for 16 S rRNA gene of bacteria were: Prokaryote V3-Forward having Oligo Sequence (5ʹ to 3ʹ) CCTACGGGNBGCASCAG and Prokaryote V4-Reverse having Oligo Sequence (5ʹ to 3ʹ) GACTACNVGGGTATCTAATCC. The primers were amplified in the PrimeX facility. The amplicon libraries were purified by 1X AMpure XP beads, checked on Agilent DNA1000 chip on Bioanalyzer2100 and quantified by Qubit Fluorometer 2.0 using Qubit dsDNA HS Assay kit (Life Technologies). After obtaining the Qubit concentration for the library and the mean peak size from Bioanalyzer profile, library was loaded onto Illumina platform at concentration range of 10–20 pM for cluster generation and sequencing. Paired-end sequencing allows the template fragments to be sequenced in both the forward and reverse directions on Illumina platform. The libraries were prepared from given samples after amplifying V3-V4 region 16S segment. Library (629 bp) were sequenced using the Illumina 2 × 250 bp sequencing chemistry to generate ~150 Mb of data per library. The next generation sequencing was performed using 2 × 250 PE chemistry on the Illumina platform. Paired-end sequence assembly was carried out for data generated using FLASH (Fast Length Adjustment of Short reads) with parameter minimum overlap of 10 bases assembler to merge paired-end reads from next-generation sequencing experiments. QIIME (Quantitative Insight Into Microbial Ecology) was used for analyzing 16S metagenome data from NGS platforms.