Microbial communities in polychlorinated biphenyl (PCB)-contaminated wastewater lagoon sediments: PCB congener, quantitative PCR, and 16S rRNA gene amplicon sequencing datasets

ABSTRACT Previous studies have demonstrated that metal-reducing microorganisms can effectively promote the precipitation and removal of uranium from contaminated groundwater. Microbial communities were stimulated in the acidic subsurface by pH neutralization and addition of an electron donor to wells. In single-well push-pull tests at a number of treated sites, nitrate, Fe(III), and uranium were extensively reduced and electron donors (glucose, ethanol) were consumed. Examination of sediment chemistry in cores sampled immediately adjacent to treated wells 3.5 months after treatment revealed that sediment pH increased substantially (by 1 to 2 pH units) while nitrate was largely depleted. A large diversity of 16S rRNA gene sequences were retrieved from subsurface sediments, including species from the α, β, δ, and γ subdivisions of the class Proteobacteria, as well as low- and high-G+C gram-positive species. Following in situ biostimulation of microbial communities within contaminated sediments, sequences related to previously cultured metal-reducing δ-Proteobacteria increased from 5% to nearly 40% of the clone libraries. Quantitative PCR revealed that Geobacter-type 16S rRNA gene sequences increased in biostimulated sediments by 1 to 2 orders of magnitude at two of the four sites tested. Evidence from the quantitative PCR analysis corroborated information obtained from 16S rRNA gene clone libraries, indicating that members of the δ-Proteobacteria subdivision, including Anaeromyxobacter dehalogenans-related and Geobacter-related sequences, are important metal-reducing organisms in acidic subsurface sediments. This study provides the first cultivation-independent analysis of the change in metal-reducing microbial communities in subsurface sediments during an in situ bioremediation experiment.

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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

Microbiology Resource Announcements ◽

10.1128/mra.00801-19 ◽

2019 ◽

Vol 8 (36) ◽

Cited By ~ 1

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.

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Investigation of Detection Limits and the Influence of DNA Extraction and Primer Choice on the Observed Microbial Communities in Drinking Water Samples Using 16S rRNA Gene Amplicon Sequencing

Frontiers in Microbiology ◽

10.3389/fmicb.2018.02140 ◽

2018 ◽

Vol 9 ◽

Cited By ~ 11

Author(s):

Jakob Brandt ◽

Mads Albertsen

Keyword(s):

Drinking Water ◽

16S Rrna ◽

16S Rrna Gene ◽

Microbial Communities ◽

Dna Extraction ◽

Water Samples ◽

Detection Limits ◽

Amplicon Sequencing ◽

Rrna Gene ◽

Drinking Water Samples

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

BMC Microbiology ◽

10.1186/s12866-021-02377-x ◽

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.

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High-resolution ISR amplicon sequencing reveals personalized oral microbiome

10.1101/320564 ◽

2018 ◽

Author(s):

Chiranjit Mukherjee ◽

Clifford J. Beall ◽

Ann L. Griffen ◽

Eugene J. Leys

Keyword(s):

High Resolution ◽

16S Rrna ◽

16S Rrna Gene ◽

Microbial Communities ◽

Cost Effective ◽

Amplicon Sequencing ◽

Species Level ◽

Rrna Gene ◽

Oral Microbiota ◽

Community Fingerprinting

AbstractBackground:Sequencing of the 16S rRNA gene has been the standard for studying the composition of microbial communities. While it allows identification of bacteria at the level of species, it does not usually provide sufficient information to resolve at the sub-species level. Species-level resolution is not adequate for studies of transmission or stability, or for exploring subspecies variation in disease association. Current approaches using whole metagenome shotgun sequencing require very high coverage that can be cost-prohibitive and computationally challenging for diverse communities. Thus there is a need for high-resolution, yet cost-effective, high-throughput methods for characterizing microbial communities.Results:Significant improvement in resolution for amplicon-based bacterial community analysis was achieved by combining amplicon sequencing of a high-diversity marker gene, the ribosomal operon ISR, with a probabilistic error modeling algorithm, DADA2. The resolving power of this new approach was compared to that of both standard and high-resolution 16S-based approaches using a set of longitudinal subgingival plaque samples. The ISR strategy achieved a 5.2-fold increase in community richness compared to reference-based 16S rRNA gene analysis, and showed 100% accuracy in predicting the correct source of a clinical sample. Individuals’ microbial communities were highly personalized, and although they exhibited some drift in membership and levels over time, that difference was always smaller than the differences between any two subjects, even after one year. The construction of an ISR database from publicly available genomic sequences allowed us to explore genomic variationwithinspecies, resulting in the identification of multiple variants of the ISR for most species.Conclusions:The ISR approach resulted in significantly improved resolution of communities, and revealed a highly personalized, stable human oral microbiota. Multiple ISR types were observed for all species examined, demonstrating a high level of subspecies variation in the oral microbiota. The approach is high-throughput, high-resolution yet cost-effective, allowing subspecies-level community fingerprinting at a cost comparable to that of 16S rRNA gene amplicon sequencing. It will be useful for a range of applications that require high-resolution identification of organisms, including microbial tracking, community fingerprinting, and potentially for identification of virulence-associated strains.

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PSXIV-23 Characterization of microbial communities associated with the rumen lining, digesta and rumen fluid from beef cattle consuming a high energy diet using 16S rRNA gene amplicon sequencing

Journal of Animal Science ◽

10.1093/jas/skz258.878 ◽

2019 ◽

Vol 97 (Supplement_3) ◽

pp. 446-446

Author(s):

Arquimides Reyes ◽

Margaret Weinroth ◽

Cory Wolfe ◽

Robert Delmore ◽

Terry Engle ◽

...

Keyword(s):

16S Rrna ◽

16S Rrna Gene ◽

Beef Cattle ◽

Microbial Communities ◽

Relative Abundance ◽

Rumen Fluid ◽

Amplicon Sequencing ◽

High Energy ◽

Feedlot Cattle ◽

Rrna Gene

Abstract The true etiology of liver abscesses is not well known. Therefore, the objective of this study was to characterize the microbial communities in the rumen lining, digesta, and rumen fluid from beef cattle consuming a high energy diet, using 16S rRNA gene amplicon sequencing. Twelve crossbred feedlot steers (450 ±10 kg; ~ 3.0 years of age) fitted with ruminal fistulas, consuming a high energy finishing diet (1.43 NEg, Mcal/kg DM) for 21 d were utilized in this experiment. Microbial DNA from three regions within the rumen [rumen lining (ventral/lateral), digesta (geometric center of the rumen), and rumen fluid] was extracted and the V4 region of the 16S rRNA gene was amplified and sequenced. Across all sample regions, bacterial sequences were classified into 34 phyla, 76 classes, 143 orders, and 254 families. Bacteroidetes and Firmicutes were the predominant phyla present across all samples. The relative abundance of Bacteroidetes detected in rumen fluid was lesser (P < 0.05) when compared to bacteria sampled from the rumen lining and digesta. In contrast, the relative abundance of Firmicutes were greater (P < 0.05) in rumen fluid and the rumen lining when compared to digesta samples. There are very few publications describing the complex community of the rumen microbiome. To our knowledge this is the first publication categorizing microbial populations in three distinct locations within the rumen using next generation sequencing in feedlot cattle.

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Influence of heavy metals on rhizosphere microbial communities of Siam weed ( Chromolaena odorata (L.)) using a 16S rRNA gene amplicon sequencing approach

Agriculture and Natural Resources ◽

10.1016/j.anres.2016.05.005 ◽

2017 ◽

Vol 51 (3) ◽

pp. 137-141 ◽

Cited By ~ 1

Author(s):

Thanyaporn Ruangdech ◽

Manoosak Wongphatcharachai ◽

Christopher Staley ◽

Michael J. Sadowsky ◽

Kannika Sajjaphan

Keyword(s):

Heavy Metals ◽

16S Rrna ◽

16S Rrna Gene ◽

Microbial Communities ◽

Amplicon Sequencing ◽

Rrna Gene ◽

Chromolaena Odorata

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Minimizing spurious features in 16S rRNA gene amplicon sequencing

10.7287/peerj.preprints.26872v1 ◽

2018 ◽

Cited By ~ 3

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.

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Minimizing spurious features in 16S rRNA gene amplicon sequencing

10.7287/peerj.preprints.26872 ◽

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.

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Much ado about nothing? Off-target amplification can lead to false-positive bacterial brain microbiome detection in healthy and Parkinson’s disease individuals

Microbiome ◽

10.1186/s40168-021-01012-1 ◽

2021 ◽

Vol 9 (1) ◽

Author(s):

Janis R. Bedarf ◽

Naiara Beraza ◽

Hassan Khazneh ◽

Ezgi Özkurt ◽

David Baker ◽

...

Keyword(s):

Parkinson’S Disease ◽

16S Rrna ◽

16S Rrna Gene ◽

False Positive ◽

Gene Sequencing ◽

Bacterial Biomass ◽

16S Rrna Gene Sequencing ◽

Amplicon Sequencing ◽

Rrna Gene ◽

Rrna Gene Sequencing

Abstract Background Recent studies suggested the existence of (poly-)microbial infections in human brains. These have been described either as putative pathogens linked to the neuro-inflammatory changes seen in Parkinson’s disease (PD) and Alzheimer’s disease (AD) or as a “brain microbiome” in the context of healthy patients’ brain samples. Methods Using 16S rRNA gene sequencing, we tested the hypothesis that there is a bacterial brain microbiome. We evaluated brain samples from healthy human subjects and individuals suffering from PD (olfactory bulb and pre-frontal cortex), as well as murine brains. In line with state-of-the-art recommendations, we included several negative and positive controls in our analysis and estimated total bacterial biomass by 16S rRNA gene qPCR. Results Amplicon sequencing did detect bacterial signals in both human and murine samples, but estimated bacterial biomass was extremely low in all samples. Stringent reanalyses implied bacterial signals being explained by a combination of exogenous DNA contamination (54.8%) and false positive amplification of host DNA (34.2%, off-target amplicons). Several seemingly brain-enriched microbes in our dataset turned out to be false-positive signals upon closer examination. We identified off-target amplification as a major confounding factor in low-bacterial/high-host-DNA scenarios. These amplified human or mouse DNA sequences were clustered and falsely assigned to bacterial taxa in the majority of tested amplicon sequencing pipelines. Off-target amplicons seemed to be related to the tissue’s sterility and could also be found in independent brain 16S rRNA gene sequences. Conclusions Taxonomic signals obtained from (extremely) low biomass samples by 16S rRNA gene sequencing must be scrutinized closely to exclude the possibility of off-target amplifications, amplicons that can only appear enriched in biological samples, but are sometimes assigned to bacterial taxa. Sequences must be explicitly matched against any possible background genomes present in large quantities (i.e., the host genome). Using close scrutiny in our approach, we find no evidence supporting the hypothetical presence of either a brain microbiome or a bacterial infection in PD brains.

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