scholarly journals Evaluating the Impact of Wastewater Effluent on Microbial Communities in the Panke, an Urban River

Water ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 888 ◽  
Author(s):  
Marcella Nega ◽  
Burga Braun ◽  
Sven Künzel ◽  
Ulrich Szewzyk
Keyword(s):  
Microbial Community ◽  
16S Rrna ◽  
16S Rrna Gene ◽  
Sampling Site ◽  
River Sediments ◽  
Microbial Community Composition ◽  
Rrna Gene ◽  
Sequencing Data ◽  
Alpha And Beta Diversity ◽  
The Impact

Pharmaceuticals are consumed in high amounts and can enter as emerging organic compounds in surface waters as they are only partially retained in wastewater treatment plants (WWTPs). Receiving pharmaceuticals may burden the aquatic environment, as they are designed to be bioactive even at low concentrations. Sediment biofilm populations were analyzed in river sediments due to the exposure of an inflow of WWTP effluents. Illumina MiSeq 16S rRNA gene amplicon sequencing was performed of 108 sediment samples, which were taken from multiple cores within three sampling locations in the Panke River, with one sampling site located downstream of the inflow. Sequencing data were processed to infer microbial community structure in samples concerning the environmental variables, such as micropollutants and physicochemical parameters measured for each core. More than 25 different micropollutants were measured in pore water samples, in which bezafibrate, clofibric acid, carbamazepine, and diclofenac were detected at high concentrations. Bacterial 16S rRNA gene amplicons revealed Nitrospirae, Proteobacteria, Chloroflexi, Actinobacteria, Acidobacteria, Bacteroidetes, and Ignavibacteriae as the most abundant groups in the samples. Differences in microbial community composition were observed with respect to micropollutants. However, our findings revealed that the composition of the microbial community was not only governed by the effluent. The significant changes in the alpha- and beta-diversity were explained by phenobarbital and SO42−, which did not originate from the WWTP indicating that more unobserved factors are also likely to play a role in affecting the biofilm community’s composition.

scholarly journals Changes in the Active, Dead, and Dormant Microbial Community Structure across a Pleistocene Permafrost Chronosequence

2019 ◽  
Vol 85 (7) ◽  
Author(s):  
Alexander Burkert ◽  
Thomas A. Douglas ◽  
Mark P. Waldrop ◽  
Rachel Mackelprang
Keyword(s):  
Microbial Community ◽  
16S Rrna ◽  
16S Rrna Gene ◽  
Microbial Communities ◽  
Community Composition ◽  
Environmental Conditions ◽  
Microbial Community Composition ◽  
Rrna Gene ◽  
Subzero Temperatures ◽  
Dormant Cells

ABSTRACTPermafrost hosts a community of microorganisms that survive and reproduce for millennia despite extreme environmental conditions, such as water stress, subzero temperatures, high salinity, and low nutrient availability. Many studies focused on permafrost microbial community composition use DNA-based methods, such as metagenomics and 16S rRNA gene sequencing. However, these methods do not distinguish among active, dead, and dormant cells. This is of particular concern in ancient permafrost, where constant subzero temperatures preserve DNA from dead organisms and dormancy may be a common survival strategy. To circumvent this, we applied (i) LIVE/DEAD differential staining coupled with microscopy, (ii) endospore enrichment, and (iii) selective depletion of DNA from dead cells to permafrost microbial communities across a Pleistocene permafrost chronosequence (19,000, 27,000, and 33,000 years old). Cell counts and analysis of 16S rRNA gene amplicons from live, dead, and dormant cells revealed how communities differ between these pools, how they are influenced by soil physicochemical properties, and whether they change over geologic time. We found evidence that cells capable of forming endospores are not necessarily dormant and that members of the classBacilliwere more likely to form endospores in response to long-term stressors associated with permafrost environmental conditions than members of theClostridia, which were more likely to persist as vegetative cells in our older samples. We also found that removing exogenous “relic” DNA preserved within permafrost did not significantly alter microbial community composition. These results link the live, dead, and dormant microbial communities to physicochemical characteristics and provide insights into the survival of microbial communities in ancient permafrost.IMPORTANCEPermafrost soils store more than half of Earth’s soil carbon despite covering ∼15% of the land area (C. Tarnocai et al., Global Biogeochem Cycles 23:GB2023, 2009, https://doi.org/10.1029/2008GB003327). This permafrost carbon is rapidly degraded following a thaw (E. A. G. Schuur et al., Nature 520:171–179, 2015, https://doi.org/10.1038/nature14338). Understanding microbial communities in permafrost will contribute to the knowledge base necessary to understand the rates and forms of permafrost C and N cycling postthaw. Permafrost is also an analog for frozen extraterrestrial environments, and evidence of viable organisms in ancient permafrost is of interest to those searching for potential life on distant worlds. If we can identify strategies microbial communities utilize to survive in permafrost, it may yield insights into how life (if it exists) survives in frozen environments outside of Earth. Our work is significant because it contributes to an understanding of how microbial life adapts and survives in the extreme environmental conditions in permafrost terrains.

Organotrophic and Mixotrofic Sulfur Oxidation in an Acidic Salt Flat in Northern Chile

2015 ◽  
Vol 1130 ◽  
pp. 63-66 ◽  
Author(s):  
Lorena Escudero ◽  
Jonathan Bijman ◽  
Guajardo M. Mariela ◽  
Juan José Pueyo Mur ◽  
Guillermo Chong ◽  
...  
Keyword(s):  
Microbial Community ◽  
16S Rrna ◽  
16S Rrna Gene ◽  
Microbial Community Composition ◽  
Iron Concentration ◽  
Rrna Gene ◽  
Salt Flat ◽  
Significant Difference ◽  
Acidic Salt ◽  
The 16S Rrna Gene

To understand the microbial community inhabiting in an acidic salt flat the phylogenetic diversity and the geochemistry of this system was compared to acid mine drainage (AMD) systems. The microbial community structure was assessed by DNA extraction/PCR/DGGE and secuencing for the 16S rRNA gene and the geochemistry was analyzed using several approaches. Prediction of metagenome functional content was performed from the 16S rRNA gene survey using the bioinformatics software package Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt). The geochemical results revealed a much lower iron concentration in the salt flat than in AMD systems (39 and 21804 mg L-1, respectively) and a significant difference in chloride levels. Sequences inferred to be from potential sulfur metabolizing organisms constituted up to 70% of the microbial community in the acidic salt flat meanwhile predominat iron-metabolizing acidophile populations were reported in AMD systems. Interestingly, the microbial assemblage in the acidic salt flat was dominated by mixotrophic and organotrophic sulfur oxidizers as well as by photoautotrophic acidophiles. Our results suggests that the salt concentration in Salar de Gorbea (average Cl-= 40 gL-1) is in the limit for the occurrence of chemolithotrophic oxidation of sulfur compounds. In addition, the investigation allows concluding that salinity rather than extremes of pH is the major environmental determinant of microbial community composition.

scholarly journals Microbial Community Composition and Diversity via 16S rRNA Gene Amplicons: Evaluating the Illumina Platform

PLoS ONE ◽  
2015 ◽  
Vol 10 (2) ◽  
pp. e0116955 ◽  
Author(s):  
Lucas Sinclair ◽  
Omneya Ahmed Osman ◽  
Stefan Bertilsson ◽  
Alexander Eiler
Keyword(s):  
Microbial Community ◽  
16S Rrna ◽  
16S Rrna Gene ◽  
Community Composition ◽  
Microbial Community Composition ◽  
Rrna Gene ◽  
Illumina Platform

scholarly journals Microbial community composition and diversity via 16S rRNA gene amplicons: evaluating the Illumina platform

2014 ◽  
Author(s):  
Lucas Sinclair ◽  
Omneya Ahmed Osman ◽  
Stefan Bertilsson ◽  
Alexander Eiler
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Beta Diversity ◽  
Sequence Data ◽  
Soda Lakes ◽  
Microbial Community Composition ◽  
Rrna Gene ◽  
Clustering Methods ◽  
Illumina Platform ◽  
Alpha And Beta Diversity

As new sequencing technologies become cheaper and older ones disappear, laboratories switch vendors and platforms. Validating the new setups is a crucial part of conducting rigorous scientific research. Here we report on the reliability and biases of performing bacterial 16S rRNA gene amplicon paired-end sequencing on the MiSeq Illumina platform. We designed a protocol using 50 barcode pairs to run samples in parallel and coded a pipeline to process the data. Sequencing the same sediment sample in 248 replicates as well as 70 samples from alkaline soda lakes, we evaluated the performance of the method with regards to estimates of alpha and beta diversity. Using different purification and DNA quantification procedures we always found up to 5-fold differences in the yield of sequences between individually barcodes samples. Using either a one-step or a two-step PCR preparation resulted in significantly different estimates in both alpha and beta diversity. Comparing with a previous method based on 454 pyrosequencing, we found that our Illumina protocol performed in a similar manner -- with the exception for evenness estimates where correspondence between the methods was low. We further quantified the data loss at every processing step eventually accumulating to 50\% of the raw reads. When evaluating different OTU clustering methods, we observed a stark contrast between the results of QIIME with default settings and the more recent UPARSE algorithm when it comes to the number of OTUs generated. Still, overall trends in alpha and beta diversity corresponded highly using both clustering methods. Our procedure performed well considering the precisions of alpha and beta diversity estimates, with insignificant effects of individual barcodes. Comparative analyses suggest that 454 and Illumina sequence data can be combined if the same PCR protocol and bioinformatic workflows are used for describing patterns in richness, beta-diversity and taxonomic composition. (version 1.1 resubmitted to PLOS one 2014-Sept-08)

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 Changes in the Active, Dead, and Dormant Microbial Community Structure Across a Pleistocene Permafrost Chronosequence

2018 ◽  
Author(s):  
Alex Burkert ◽  
Thomas A. Douglas ◽  
Mark P. Waldrop ◽  
Rachel Mackelprang
Keyword(s):  
Microbial Community ◽  
16S Rrna ◽  
16S Rrna Gene ◽  
Microbial Communities ◽  
Community Composition ◽  
Environmental Conditions ◽  
Microbial Community Composition ◽  
Rrna Gene ◽  
Subzero Temperatures ◽  
Dormant Cells

AbstractPermafrost hosts a community of microorganisms that survive and reproduce for millennia despite extreme environmental conditions such as water stress, subzero temperatures, high salinity, and low nutrient availability. Many studies focused on permafrost microbial community composition use DNA-based methods such as metagenomic and 16S rRNA gene sequencing. However, these methods do not distinguish between active, dead, and dormant cells. This is of particular concern in ancient permafrost where constant subzero temperatures preserve DNA from dead organisms and dormancy may be a common survival strategy. To circumvent this we applied: (i) live/dead differential staining coupled with microscopy, (ii) endospore enrichment, and (iii) selective depletion of DNA from dead cells to permafrost microbial communities across a Pleistocene permafrost chronosequence (19K, 27K, and 33K). Cell counts and analysis of 16S rRNA gene amplicons from live, dead, and dormant cells revealed how communities differ between these pools and how they change over geologic time. We found clear evidence that cells capable of forming endospores are not necessarily dormant and that the propensity to form endospores differed among taxa. Specifically, Bacilli are more likely to form endospores in response to long-term stressors associated with permafrost environmental conditions than members of Clostridia, which are more likely to persist as vegetative cells over geologic timescales. We also found that exogenous DNA preserved within permafrost does not bias DNA sequencing results since its removal did not significantly alter the microbial community composition. These results extend the findings of a previous study that showed permafrost age and ice content largely control microbial community diversity and cell abundances.ImportanceThe study of permafrost transcends the study of climate change and exobiology. Permafrost soils store more than half earth’s soil carbon despite covering ∽15% of the land area (Tarnocai et al 2009). This permafrost carbon is rapidly degraded following thaw (Tarnocai C et al 2009, Schuur et al 2015). Understanding microbial communities in permafrost will contribute to the knowledge base necessary to understand the rates and forms of permafrost C and N cycling post thaw. Permafrost is also an analog for frozen extraterrestrial environments and evidence of viable organisms in ancient permafrost is of interest to those searching for potential life on distant worlds. If we can identify strategies microbial communities utilize to survive permafrost we can focus efforts searching for evidence of life on cryogenic cosmic bodies. Our work is significant because it contributes to an understanding of how microbial life adapts and survives in the extreme environmental conditions in permafrost terrains across geologic timescales.

scholarly journals Gastrointestinal Segments Influenced Fermentation End-Products, Microbiota and Microbial Abundances in Goats

2021 ◽  
Author(s):  
Tsegay Gebremariam ◽  
Zhiliang Tan
Keyword(s):  
Fatty Acids ◽  
Microbial Community ◽  
16S Rrna ◽  
16S Rrna Gene ◽  
18S Rrna ◽  
18S Rrna Gene ◽  
Rrna Gene ◽  
Gene Copies ◽  
End Products ◽  
The Impact

Abstract Purpose: Carbohydrate diets altered fermentation end-products and microbial community in the gastrointestinal tracts (GIT) of goats. Gastrointestinal contents used to determine the impact of carbohydrate feeds on fermentation end-products and microbial community in goats.Methodology: in the study goats were assigned to one of the two treatments corn meal (CM) or Corn gluten (CG) in a randomized block design (400 g/kg DM each). Goats were slaughtered, GIT liquids were used to determine dissolved gasses, fatty acids and microbial community.Results: Goats fed CG increased molar acetate (P < 0.05), lowered butyrate and propionate in the fore and hindgut comparing to those goats received CM. Goats received CM had higher (P < 0.05) dH2 while lowered dH2S in the fore and hindgut than those goats fed with CG treatment. The fore and hindgut had higher (P < 0.01) 16S rRNA gene copies of bacteria, protozoa, methanogens and 18S rRNA gene copies fungi than in the ileum and cecum. Goats fed CG diet had higher (P < 0.05)16S rRNA gene copies of bacteria, protozoa, methanogens, and 18S rRNA gene copies of fungi than those goats fed with CM diet. Conclusion fore and hindguts improved dissolved gasses, fatty acids and microbial community comparing with in the ileum and cecum. Goats fed CM had improved the Methanobacterials order and Methanobrevibacter genus as compared with those goats fed CG. The study suggested that hindgut segments have a reasonable contribution as foregut to methane emissions from goats.

scholarly journals Biogeography and Biodiversity in Sulfide Structures of Active and Inactive Vents at Deep-Sea Hydrothermal Fields of the Southern Mariana Trough

2010 ◽  
Vol 76 (9) ◽  
pp. 2968-2979 ◽  
Author(s):  
Shingo Kato ◽  
Yoshinori Takano ◽  
Takeshi Kakegawa ◽  
Hironori Oba ◽  
Kazuhiko Inoue ◽  
...  
Keyword(s):  
Microbial Community ◽  
16S Rrna ◽  
16S Rrna Gene ◽  
Microbial Communities ◽  
Microbial Community Composition ◽  
Organic Content ◽  
Hyperthermophilic Archaea ◽  
Spreading Center ◽  
Rrna Gene ◽  
Hydrothermal Fields

ABSTRACT The abundance, diversity, activity, and composition of microbial communities in sulfide structures both of active and inactive vents were investigated by culture-independent methods. These sulfide structures were collected at four hydrothermal fields, both on- and off-axis of the back-arc spreading center of the Southern Mariana Trough. The microbial abundance and activity in the samples were determined by analyzing total organic content, enzymatic activity, and copy number of the 16S rRNA gene. To assess the diversity and composition of the microbial communities, 16S rRNA gene clone libraries including bacterial and archaeal phylotypes were constructed from the sulfide structures. Despite the differences in the geological settings among the sampling points, phylotypes related to the Epsilonproteobacteria and cultured hyperthermophilic archaea were abundant in the libraries from the samples of active vents. In contrast, the relative abundance of these phylotypes was extremely low in the libraries from the samples of inactive vents. These results suggest that the composition of microbial communities within sulfide structures dramatically changes depending on the degree of hydrothermal activity, which was supported by statistical analyses. Comparative analyses suggest that the abundance, activity and diversity of microbial communities within sulfide structures of inactive vents are likely to be comparable to or higher than those in active vent structures, even though the microbial community composition is different between these two types of vents. The microbial community compositions in the sulfide structures of inactive vents were similar to those in seafloor basaltic rocks rather than those in marine sediments or the sulfide structures of active vents, suggesting that the microbial community compositions on the seafloor may be constrained by the available energy sources. Our findings provide helpful information for understanding the biogeography, biodiversity and microbial ecosystems in marine environments.

scholarly journals An inter-laboratory study to investigate the impact of the bioinformatics component on microbiome analysis using mock communities

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Denise M. O’Sullivan ◽  
Ronan M. Doyle ◽  
Sasithon Temisak ◽  
Nicholas Redshaw ◽  
Alexandra S. Whale ◽  
...  
Keyword(s):  
Microbial Community ◽  
16S Rrna ◽  
16S Rrna Gene ◽  
Relative Abundance ◽  
Amplicon Sequencing ◽  
16S Rrna Genes ◽  
Rrna Genes ◽  
Rrna Gene ◽  
Microbiome Analysis ◽  
The Impact

AbstractDespite the advent of whole genome metagenomics, targeted approaches (such as 16S rRNA gene amplicon sequencing) continue to be valuable for determining the microbial composition of samples. Amplicon microbiome sequencing can be performed on clinical samples from a normally sterile site to determine the aetiology of an infection (usually single pathogen identification) or samples from more complex niches such as human mucosa or environmental samples where multiple microorganisms need to be identified. The methodologies are frequently applied to determine both presence of micro-organisms and their quantity or relative abundance. There are a number of technical steps required to perform microbial community profiling, many of which may have appreciable precision and bias that impacts final results. In order for these methods to be applied with the greatest accuracy, comparative studies across different laboratories are warranted. In this study we explored the impact of the bioinformatic approaches taken in different laboratories on microbiome assessment using 16S rRNA gene amplicon sequencing results. Data were generated from two mock microbial community samples which were amplified using primer sets spanning five different variable regions of 16S rRNA genes. The PCR-sequencing analysis included three technical repeats of the process to determine the repeatability of their methods. Thirteen laboratories participated in the study, and each analysed the same FASTQ files using their choice of pipeline. This study captured the methods used and the resulting sequence annotation and relative abundance output from bioinformatic analyses. Results were compared to digital PCR assessment of the absolute abundance of each target representing each organism in the mock microbial community samples and also to analyses of shotgun metagenome sequence data. This ring trial demonstrates that the choice of bioinformatic analysis pipeline alone can result in different estimations of the composition of the microbiome when using 16S rRNA gene amplicon sequencing data. The study observed differences in terms of both presence and abundance of organisms and provides a resource for ensuring reproducible pipeline development and application. The observed differences were especially prevalent when using custom databases and applying high stringency operational taxonomic unit (OTU) cut-off limits. In order to apply sequencing approaches with greater accuracy, the impact of different analytical steps needs to be clearly delineated and solutions devised to harmonise microbiome analysis results.

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