scholarly journals Minimizing spurious features in 16S rRNA gene amplicon sequencing

2018 ◽  
Author(s):  
Jing Wang ◽  
Qianpeng Zhang ◽  
Guojun Wu ◽  
Chenhong Zhang ◽  
Menghui Zhang ◽  
...  
Keyword(s):  
Data Analysis ◽  
16S Rrna ◽  
16S Rrna Gene ◽  
Microbial Communities ◽  
Simulated Data ◽  
Amplicon Sequencing ◽  
Rrna Gene ◽  
Sequencing Data ◽  
The Real ◽  
Matthew’S Correlation Coefficient

The 16S rRNA gene amplicon sequencing is a widely used high-throughput method for the taxonomic inference in microbial communities. Many data analysis pipelines have been developed to enhance the accuracy in reflecting the real taxonomy, in order to better guide the downstream identification, isolation and mechanistic studies. Though rigorous quality filtration steps were adopted in these pipelines, with well-designed mock and simulated data sets, we found that there were still a widely divergent number of spurious features due to the “pseudo sequences” artificially generated during the PCR and sequencing process. These pseudo sequences were in low abundances, and were unreliable determined through a weighted re-sampling test. To minimize their influences on the characterization of taxonomy, we proposed an approach that contains two steps, an abundance filtering (AF) step and the subsequent AF-based OTU picking and remapping (AOR) step, which can efficiently decrease the spurious OTUs, sequences or oligotyping features, and improve Matthew's Correlation Coefficient (MCC) values in OTU clustering. The approach can be easily integrated with the popularly-used 16S rRNA sequencing data analysis pipelines, to make the number of OTUs, alpha and beta diversities from divergent pipelines more consistent with the real structure of microbial communities.

scholarly journals Minimizing spurious features in 16S rRNA gene amplicon sequencing

2018 ◽  
Author(s):  
Jing Wang ◽  
Qianpeng Zhang ◽  
Guojun Wu ◽  
Chenhong Zhang ◽  
Menghui Zhang ◽  
...  
Keyword(s):  
Data Analysis ◽  
16S Rrna ◽  
16S Rrna Gene ◽  
Microbial Communities ◽  
Simulated Data ◽  
Amplicon Sequencing ◽  
Rrna Gene ◽  
Sequencing Data ◽  
The Real ◽  
Matthew’S Correlation Coefficient

The 16S rRNA gene amplicon sequencing is a widely used high-throughput method for the taxonomic inference in microbial communities. Many data analysis pipelines have been developed to enhance the accuracy in reflecting the real taxonomy, in order to better guide the downstream identification, isolation and mechanistic studies. Though rigorous quality filtration steps were adopted in these pipelines, with well-designed mock and simulated data sets, we found that there were still a widely divergent number of spurious features due to the “pseudo sequences” artificially generated during the PCR and sequencing process. These pseudo sequences were in low abundances, and were unreliable determined through a weighted re-sampling test. To minimize their influences on the characterization of taxonomy, we proposed an approach that contains two steps, an abundance filtering (AF) step and the subsequent AF-based OTU picking and remapping (AOR) step, which can efficiently decrease the spurious OTUs, sequences or oligotyping features, and improve Matthew's Correlation Coefficient (MCC) values in OTU clustering. The approach can be easily integrated with the popularly-used 16S rRNA sequencing data analysis pipelines, to make the number of OTUs, alpha and beta diversities from divergent pipelines more consistent with the real structure of microbial communities.

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.

scholarly journals 16S rRNA Gene Amplicon Sequencing of Microbial Communities Involved in Anaerobic Bulking in a Mesophilic Expanded Granular Sludge Bed Reactor Treating Wastewater Discharged from a Japanese-Style Thickened Worcestershire Sauce-Producing Factory

2019 ◽  
Vol 8 (36) ◽  
Author(s):  
Takeshi Yamada ◽  
Jun Harada ◽  
Yuki Okazaki ◽  
Tsuyoshi Yamaguchi ◽  
Atsushi Nakano
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Microbial Communities ◽  
Granular Sludge ◽  
Amplicon Sequencing ◽  
Organic Content ◽  
Rrna Gene ◽  
Sludge Bulking ◽  
High Organic Content

We analyzed the prokaryotes in bulking and healthy sludge from a mesophilic expanded granular sludge bed reactor treating wastewater with high organic content by 16S rRNA gene amplicon sequencing. We tabulated the microbiota at the phylum level, providing a framework for avoiding sludge bulking.

scholarly journals 16S rRNA Gene Amplicon Sequencing Data of Tailing and Nontailing Rhizosphere Soils of Mimosa pudica from a Heavy Metal-Contaminated Ex-Tin Mining Area

2020 ◽  
Vol 9 (42) ◽  
Author(s):  
Saidu Abdullahi ◽  
Hazzeman Haris ◽  
Kamarul Z. Zarkasi ◽  
Hamzah G. Amir
Keyword(s):  
Heavy Metal ◽  
16S Rrna ◽  
16S Rrna Gene ◽  
Sequence Data ◽  
Amplicon Sequencing ◽  
Rrna Gene ◽  
Mimosa Pudica ◽  
Sequencing Data ◽  
Content Type ◽  
Rhizosphere Soils

ABSTRACT The 16S rRNA gene amplicon sequence data from tailing and nontailing rhizosphere soils of Mimosa pudica from a heavy metal-contaminated area are reported here. Diverse bacterial taxa were represented in the results, and the most dominant phyla were Proteobacteria (41.2%), Acidobacteria (17.1%), and Actinobacteria (14.4%).

scholarly journals The evolution of realized niches within freshwater Synechococcus

2019 ◽  
Author(s):  
Nicolas Tromas ◽  
Zofia E. Taranu ◽  
Mathieu Castelli ◽  
Juliana S. M. Pimentel ◽  
Daniel A. Pereira ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Environmental Parameters ◽  
Amplicon Sequencing ◽  
Fundamental Question ◽  
Rrna Gene ◽  
Biological Interactions ◽  
Sequencing Data ◽  
Evolutionary Time ◽  
Genus Level

SummaryUnderstanding how ecological traits have changed over evolutionary time is a fundamental question in biology. Specifically, the extent to which more closely-related organisms share similar ecological preferences due to phylogenetic conservation – or if they are forced apart by competition – is still debated. Here we explored the co-occurrence patterns of freshwater cyanobacteria at the sub-genus level to investigate whether more closely-related taxa share more similar niches, and to what extent these niches were defined by abiotic or biotic variables. We used deep 16S rRNA gene amplicon sequencing and measured several abiotic environmental parameters (nutrients, temperature, etc.) in water samples collected over time and space in Furnas Reservoir, Brazil. We found that relatively more closely-related Synechococcus (in the continuous range of 93-100% nucleotide identity in 16S) had an increased tendency to co-occur with one another (i.e. had similar realized niches). This tendency could not be easily explained by shared preferences for measured abiotic niche dimensions. Thus, commonly measured abiotic parameters might not be sufficient to characterize, nor to predict community assembly or dynamics. Rather, co-occurrence between Synechococcus and the surrounding community (whether or not they represent true biological interactions) may be a more sensitive measure of realized niches. Overall, our results suggest that realized niches are phylogenetically conserved, at least at the sub-genus level and at the resolution of the 16S marker. Determining how these results generalize to other genera and at finer genetic resolution merits further investigation.Originality-Significance StatementWe address a fundamental question in ecology and evolution: how do niche preferences change over evolutionary time? Using time-series analysis of 16S rRNA gene amplicon sequencing data, we develop an approach to highlight the importance of biotic factors in defining realized niches, and show how niche preferences change proportionally with the 16S gene molecular clock within the genus Synechococcus. Ours is also one of few studies on the ecology of freshwater Synechococcus, adding significantly to our knowledge about this abundant and widespread lineage of Cyanobacteria.

scholarly journals The archives are half-empty: a field-wide assessment of the availability of microbial community sequencing data

2020 ◽  
Author(s):  
Stephanie D. Jurburg ◽  
Maximilian Konzack ◽  
Nico Eisenhauer ◽  
Anna Heintz-Buschart
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Amplicon Sequencing ◽  
Data Reuse ◽  
Rrna Gene ◽  
Data Loss ◽  
Sequencing Data ◽  
Data Archiving ◽  
The 16S Rrna Gene ◽  
Over Time

AbstractThe sequencing revolution has resulted in the explosive growth of public genetic repositories. These repositories now hold invaluable collections of 16S rRNA gene amplicon sequences, but the extent to which the currently archived data is findable, accessible, and reusable has not been evaluated. We conducted a field-wide assessment of the availability and state of publicly archived 16S rRNA gene amplicon sequencing data. Using custom-built pattern-based text extraction algorithms, we searched 26,927 publications in 17 microbiology or microbial ecology journals, and identified 2,015 studies which performed 16S rRNA gene amplicon sequencing. We found, for example, that 7.2% of these had not been made public at the time of analysis, a trend which increased over time. Of the 635 studies targeting the V3-V4 region of the 16S rRNA gene, 40.3% contained data which was not available or not reusable, and for 25.5% of the studies, faults in data formatting or data labelling were likely to create obstacles in data reuse. Taken together, only 34% of these datasets had potentially reusable data. Our study reveals significant gaps in the availability of currently deposited community sequencing data, identifies major contributors to data loss, and offers suggestions for improving data archiving practices in the future.

scholarly journals Rabbit microbiota across the whole body revealed by 16S rRNA gene amplicon sequencing

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xiaofen Hu ◽  
Fei Wang ◽  
Shanshan Yang ◽  
Xu Yuan ◽  
Tingyu Yang ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Microbial Communities ◽  
Amplicon Sequencing ◽  
Whole Body ◽  
Rrna Gene ◽  
Microbial Function ◽  
Relationship Of ◽  
The Relationship ◽  
Microbial Samples

Abstract Background Rabbit can produce meat, fur and leather, and serves as an important biomedical animal model. Understanding the microbial community of rabbits helps to raise rabbits healthily and better support their application as animal models. Results In this study, we selected 4 healthy Belgium gray rabbits to collect the microbial samples from 12 body sites, including skin, lung, uterus, mouth, stomach, duodenum, ileum, jejunum, colon, cecum, cecal appendix and rectum. The microbiota across rabbit whole body was investigated via 16S rRNA gene amplicon sequencing. After quality control, 46 samples were retained, and 3,148 qualified ASVs were obtained, representing 23 phyla and 264 genera. Based on the weighted UniFrac distances, these samples were divided into the large intestine (Lin), stomach and small intestine (SSin), uterus (Uter), and skin, mouth and lung (SML) groups. The diversity of Lin microbiota was the highest, followed by those of the SSin, Uter and SML groups. In the whole body, Firmicutes (62.37%), Proteobacteria (13.44%) and Bacteroidota (11.84%) were the most predominant phyla. The relative abundance of Firmicutes in the intestinal tract was significantly higher than that in the non-intestinal site, while Proteobacteria was significantly higher in the non-intestinal site. Among the 264 genera, 35 were the core microbiota distributed in all body sites. Sixty-one genera were specific in the SML group, while 13, 8 and 1 were specifically found in the Lin, SSin and Uter groups, respectively. The Lin group had the most difference with other groups, there were average 72 differential genera between the Lin and other groups. The functional prediction analysis showed that microbial function within each group was similar, but there was a big difference between the intestinal tracts and the non-intestinal group. Notably, the function of microorganism in uterus and mouth were the most different from those in the gastrointestinal sites; rabbit’s coprophagy of consuming soft feces possibly resulted in little differences of microbial function between stomach and large intestinal sites. Conclusion Our findings improve the knowledge about rabbit microbial communities throughout whole body and give insights into the relationship of microbial communities among different body sites in health rabbits.

scholarly journals Updating urinary microbiome analyses to enhance biologic interpretation

2021 ◽  
Author(s):  
Nazema Y Siddiqui ◽  
Li Ma ◽  
Linda Brubaker ◽  
Jialiang Mao ◽  
Carter Hoffman ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Microbial Communities ◽  
Bacterial Genome ◽  
Rrna Gene ◽  
Sequence Variant ◽  
Sequencing Data ◽  
Variable Regions ◽  
Urinary Microbiome ◽  
The Impact

Objective: An approach for assessing the urinary microbiome is 16S rRNA gene sequencing, where a segment of the bacterial genome is amplified and sequenced. Methods used to analyze these data are rapidly evolving, although the research implications are not known. This re-analysis of an existing dataset aimed to determine the impact of updated bioinformatic and statistical techniques. Methods: A prior Pelvic Floor Disorders Network (PFDN) study compared the urinary microbiome in 123 women with mixed urinary incontinence (MUI) and 84 controls. We used the PFDN unprocessed sequencing data of V1-V3 and V4-V6 16S variable regions, processed operational taxonomic unit (OTU) tables, and de-identified clinical data. We processed sequencing data with an updated bioinformatic pipeline, which used DADA2 to generate amplicon sequence variant (ASV) tables. Taxa from ASV tables were compared to OTU tables generated from the original processing; taxa from different variable regions (e.g., V1-V3 versus V4-V6) after updated processing were also compared. After updated processing, data were analyzed with multiple filtering thresholds. Several techniques were tested to cluster samples into microbial communities. Multivariable regression was used to test for associations between microbial communities and MUI, while controlling for potentially confounding variables. Results: Of taxa identified through updated bioinformatic processing, only 40% were identified originally, though taxa identified through both methods represented >99% of sequencing data in terms of relative abundance. When different 16S rRNA gene regions were sequenced from the same samples, there were differences noted in recovered taxa. When the original clustering methods were applied to reprocessed sequencing data, we confirmed differences in microbial communities associated with MUI. However, when samples were clustered with a different methodology, microbial communities were no longer associated with MUI. Conclusions: Updated bioinformatic processing techniques recover many different taxa compared to prior techniques, though most of these differences exist in low abundance taxa that occupy a small proportion of the overall microbiome. Detection of high abundance taxa are not significantly impacted by bioinformatic strategy. However, there are different biases for less abundant taxa; these differences as well as downstream clustering methodology and filtering thresholds may affect interpretation of overall results.

scholarly journals 16S rRNA Gene Amplicon Sequencing Data of the Iron Quadrangle Ferruginous Caves (Brazil) Shows the Importance of Conserving This Singular and Threatened Geosystem

Diversity ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 494
Author(s):  
Camila G. C. Lemes ◽  
Morghana M. Villa ◽  
Érica B. Felestrino ◽  
Luiza O. Perucci ◽  
Renata A. B. Assis ◽  
...  
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Microbial Diversity ◽  
Amplicon Sequencing ◽  
Rrna Gene ◽  
Sequencing Data ◽  
Metabolic Potential ◽  
Microbial Life ◽  
Iron Quadrangle ◽  
Abundance And Diversity

The Iron Quadrangle (IQ) is one of the main iron ore producing regions of the world. The exploitation of its reserves jeopardizes the high biological endemism associated with this region. This work aimed to understand the diversity and bacterial potential associated with IQ caves. Floor and ceiling samples of seven ferruginous caves and one quartzite cave were collected, and their microbial relative abundance and diversity were established by 16S rRNA gene amplicon sequencing data. The results showed that ferruginous caves present higher microbial abundance and greater microbial diversity compared to the quartzite cave. Many species belonging to genera found in these caves, such as Pseudonocardia and Streptacidiphilus, are known to produce biomolecules of biotechnological interest as macrolides and polyketides. Moreover, comparative analysis of microbial diversity and metabolic potential in a biofilm in pendant microfeature revealed that the microbiota associated with this structure is more similar to the floor rather than ceiling samples, with the presence of genera that may participate in the genesis of these cavities, for instance, Ferrovum, Geobacter, and Sideroxydans. These results provide the first glimpse of the microbial life in these environments and emphasize the need of conservation programs for these areas, which are under intense anthropogenic exploration.

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