scholarly journals Generation of Multimillion-Sequence 16S rRNA Gene Libraries from Complex Microbial Communities by Assembling Paired-End Illumina Reads

2011 ◽  
Vol 77 (11) ◽  
pp. 3846-3852 ◽  
Author(s):  
Andrea K. Bartram ◽  
Michael D. J. Lynch ◽  
Jennifer C. Stearns ◽  
Gabriel Moreno-Hagelsieb ◽  
Josh D. Neufeld
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Microbial Communities ◽  
16S Rrna Gene Sequencing ◽  
Taxonomic Diversity ◽  
Illumina Genome Analyzer ◽  
Rrna Gene ◽  
Variable Regions ◽  
Gene Libraries

ABSTRACTMicrobial communities host unparalleled taxonomic diversity. Adequate characterization of environmental and host-associated samples remains a challenge for microbiologists, despite the advent of 16S rRNA gene sequencing. In order to increase the depth of sampling for diverse bacterial communities, we developed a method for sequencing and assembling millions of paired-end reads from the 16S rRNA gene (spanning the V3 region; ∼200 nucleotides) by using an Illumina genome analyzer. To confirm reproducibility and to identify a suitable computational pipeline for data analysis, sequence libraries were prepared in duplicate for both a defined mixture of DNAs from known cultured bacterial isolates (>1 million postassembly sequences) and an Arctic tundra soil sample (>6 million postassembly sequences). The Illumina 16S rRNA gene libraries represent a substantial increase in number of sequences over all extant next-generation sequencing approaches (e.g., 454 pyrosequencing), while the assembly of paired-end 125-base reads offers a methodological advantage by incorporating an initial quality control step for each 16S rRNA gene sequence. This method incorporates indexed primers to enable the characterization of multiple microbial communities in a single flow cell lane, may be modified readily to target other variable regions or genes, and demonstrates unprecedented and economical access to DNAs from organisms that exist at low relative abundances.

scholarly journals Dynamics of Soil Microbial Communities During Diazepam and Oxazepam Biodegradation in Soil Flooded by Water From a WWTP

2021 ◽  
Vol 12 ◽  
Author(s):  
Marc Crampon ◽  
Coralie Soulier ◽  
Pauline Sidoli ◽  
Jennifer Hellal ◽  
Catherine Joulian ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Microbial Communities ◽  
Soil Microbial Communities ◽  
Gene Sequencing ◽  
16S Rrna Gene Sequencing ◽  
Treated Wastewater ◽  
Rrna Gene ◽  
Sequencing Data ◽  
Rrna Gene Sequencing

The demand for energy and chemicals is constantly growing, leading to an increase of the amounts of contaminants discharged to the environment. Among these, pharmaceutical molecules are frequently found in treated wastewater that is discharged into superficial waters. Indeed, wastewater treatment plants (WWTPs) are designed to remove organic pollution from urban effluents but are not specific, especially toward contaminants of emerging concern (CECs), which finally reach the natural environment. In this context, it is important to study the fate of micropollutants, especially in a soil aquifer treatment (SAT) context for water from WWTPs, and for the most persistent molecules such as benzodiazepines. In the present study, soils sampled in a reed bed frequently flooded by water from a WWTP were spiked with diazepam and oxazepam in microcosms, and their concentrations were monitored for 97 days. It appeared that the two molecules were completely degraded after 15 days of incubation. Samples were collected during the experiment in order to follow the dynamics of the microbial communities, based on 16S rRNA gene sequencing for Archaea and Bacteria, and ITS2 gene for Fungi. The evolution of diversity and of specific operating taxonomic units (OTUs) highlighted an impact of the addition of benzodiazepines, a rapid resilience of the fungal community and an evolution of the bacterial community. It appeared that OTUs from the Brevibacillus genus were more abundant at the beginning of the biodegradation process, for diazepam and oxazepam conditions. Additionally, Tax4Fun tool was applied to 16S rRNA gene sequencing data to infer on the evolution of specific metabolic functions during biodegradation. It finally appeared that the microbial community in soils frequently exposed to water from WWTP, potentially containing CECs such as diazepam and oxazepam, may be adapted to the degradation of persistent contaminants.

Characterization of the depth-related changes in the microbial communities in Lake Hovsgol sediment by 16S rRNA gene-based approaches

2008 ◽  
Vol 46 (2) ◽  
pp. 125-136 ◽  
Author(s):  
Young-Do Nam ◽  
Youlboong Sung ◽  
Ho-Won Chang ◽  
Seong Woon Roh ◽  
Kyoung-Ho Kim ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Microbial Communities ◽  
Rrna Gene ◽  
Lake Hovsgol

scholarly journals Highly Distinct Microbial Communities in Elevated Strings and Submerged Flarks in the Boreal Aapa-Type Mire

2022 ◽  
Vol 10 (1) ◽  
pp. 170
Author(s):  
Andrey L. Rakitin ◽  
Shahjahon Begmatov ◽  
Alexey V. Beletsky ◽  
Dmitriy A. Philippov ◽  
Vitaly V. Kadnikov ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Microbial Communities ◽  
16S Rrna Gene Sequencing ◽  
Rrna Gene ◽  
16S Rrna Gene Sequences ◽  
Raised Bogs ◽  
European North ◽  
Rrna Gene Sequencing ◽  
Surface Peat

Large areas in the northern hemisphere are covered by extensive wetlands, which represent a complex mosaic of raised bogs, eutrophic fens, and aapa mires all in proximity to each other. Aapa mires differ from other types of wetlands by their concave surface, heavily watered by the central part, as well as by the presence of large-patterned string-flark complexes. In this paper, we characterized microbial diversity patterns in the surface peat layers of the neighboring string and flark structures located within the mire site in the Vologda region of European North Russia, using 16S rRNA gene sequencing. The microbial communities in raised strings were clearly distinct from those in submerged flarks. Strings were dominated by the Alpha- and Gammaproteobacteria. Other abundant groups were the Acidobacteriota, Bacteroidota, Verrucomicrobiota, Actinobacteriota, and Planctomycetota. Archaea accounted for only 0.4% of 16S rRNA gene sequences retrieved from strings. By contrast, they comprised about 22% of all sequences in submerged flarks and mostly belonged to methanogenic lineages. Methanotrophs were nearly absent. Other flark-specific microorganisms included the phyla Chloroflexi, Spirochaetota, Desulfobacterota, Beijerinckiaceae- and Rhodomicrobiaceae-affiliated Alphaproteobacteria, and uncultivated groups env.OPS_17 and vadinHA17 of the Bacteroidota. Such pattern probably reflects local anaerobic conditions in the submerged peat layers in flarks.

Microbiota characterization of sheep milk and its association with somatic cell count using 16s rRNA gene sequencing

2019 ◽  
Vol 137 (1) ◽  
pp. 73-83 ◽  
Author(s):  
Cristina Esteban‐Blanco ◽  
Beatriz Gutiérrez‐Gil ◽  
Fernando Puente‐Sánchez ◽  
Héctor Marina ◽  
Javier Tamames ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Cell Count ◽  
Somatic Cell Count ◽  
Gene Sequencing ◽  
16S Rrna Gene Sequencing ◽  
Rrna Gene ◽  
Sheep Milk ◽  
Rrna Gene Sequencing

scholarly journals MicroPheno: Predicting environments and host phenotypes from 16S rRNA gene sequencing using a k-mer based representation of shallow sub-samples

2018 ◽  
Author(s):  
Ehsaneddin Asgari ◽  
Kiavash Garakani ◽  
Alice Carolyn McHardy ◽  
Mohammad R.K. Mofrad
Keyword(s):  
Deep Learning ◽  
16S Rrna ◽  
16S Rrna Gene ◽  
Microbial Communities ◽  
Gene Sequencing ◽  
Operational Taxonomic Unit ◽  
16S Rrna Gene Sequencing ◽  
Rrna Gene ◽  
Sequence Alignments ◽  
Rrna Gene Sequencing

Motivation: Microbial communities play important roles in the function and maintenance of various biosystems, ranging from the human body to the environment. A major challenge in microbiome research is the classification of microbial communities of different environments or host phenotypes. The most common and cost-effective approach for such studies to date is 16S rRNA gene sequencing. Recent falls in sequencing costs have increased the demand for simple, efficient, and accurate methods for rapid detection or diagnosis with proved applications in medicine, agriculture, and forensic science. We describe a reference- and alignment-free approach for predicting environments and host phenotypes from 16S rRNA gene sequencing based on k-mer representations that benefits from a bootstrapping framework for investigating the sufficiency of shallow sub-samples. Deep learning methods as well as classical approaches were explored for predicting environments and host phenotypes. Results: k-mer distribution of shallow sub-samples outperformed the computationally costly Operational Taxonomic Unit (OTU) features in the tasks of body-site identification and Crohn's disease prediction. Aside from being more accurate, using k-mer features in shallow sub-samples allows (i) skipping computationally costly sequence alignments required in OTU-picking, and (ii) provided a proof of concept for the sufficiency of shallow and short-length 16S rRNA sequencing for phenotype prediction. In addition, k-mer features predicted representative 16S rRNA gene sequences of 18 ecological environments, and 5 organismal environments with high macro-F1 scores of 0.88 and 0.87. For large datasets, deep learning outperformed classical methods such as Random Forest and SVM. Availability: The software and datasets are available at https://llp.berkeley.edu/micropheno.

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