scholarly journals Run-to-Run Sequencing Variation Can Introduce Taxon-Specific Bias in the Evaluation of Fungal Microbiomes

2018 ◽  
Vol 2 (3) ◽  
pp. 165-170 ◽  
Author(s):  
Zewei Song ◽  
Dan Schlatter ◽  
Daryl M. Gohl ◽  
Linda L. Kinkel
Keyword(s):  
Quality Control ◽  
Microbial Communities ◽  
High Throughput Sequencing ◽  
Marker Gene ◽  
Soil Samples ◽  
The Other ◽  
Potential Bias ◽  
Mock Community ◽  
Control Information ◽  
Mock Communities

The routine use of high-throughput sequencing to profile microbial communities necessitates improved protocols for detecting and adjusting for variation among sequencing runs for marker gene analysis. Although mock communities are widely used as a control among runs, the composition and diversity of mock communities, in most cases, are orders of magnitude lower than the actual samples. We demonstrated that replicated biological samples (“technical replicates”) are superior to a mock community in detecting variation and potential bias among sequencing runs. We present a case in which technical replicates of three soil samples were sequenced in three MiSeq runs containing samples from multiple experiments. The technical replicate samples revealed a potentially biased, outlier sequencing run, from which several Ascomycota taxa were substantially underestimated. Similar bias was seen in the other samples sequenced but was not detected using the mock community. Our study demonstrates that using technical replicates along with traditional mock communities provide additional quality control information and aid in detecting outlier sequencing runs.

scholarly journals Accurate Estimation of Fungal Diversity and Abundance through Improved Lineage-Specific Primers Optimized for Illumina Amplicon Sequencing

2016 ◽  
Vol 82 (24) ◽  
pp. 7217-7226 ◽  
Author(s):  
D. Lee Taylor ◽  
William A. Walters ◽  
Niall J. Lennon ◽  
James Bochicchio ◽  
Andrew Krohn ◽  
...  
Keyword(s):  
High Throughput ◽  
High Throughput Sequencing ◽  
Large Subunit ◽  
Marker Gene ◽  
Soil Samples ◽  
Gene Copy ◽  
Accurate Estimation ◽  
Rrna Gene ◽  
Data Set ◽  
Mock Communities

ABSTRACTWhile high-throughput sequencing methods are revolutionizing fungal ecology, recovering accurate estimates of species richness and abundance has proven elusive. We sought to design internal transcribed spacer (ITS) primers and an Illumina protocol that would maximize coverage of the kingdom Fungi while minimizing nontarget eukaryotes. We inspected alignments of the 5.8S and large subunit (LSU) ribosomal genes and evaluated potential primers using PrimerProspector. We tested the resulting primers using tiered-abundance mock communities and five previously characterized soil samples. We recovered operational taxonomic units (OTUs) belonging to all 8 members in both mock communities, despite DNA abundances spanning 3 orders of magnitude. The expected and observed read counts were strongly correlated (r= 0.94 to 0.97). However, several taxa were consistently over- or underrepresented, likely due to variation in rRNA gene copy numbers. The Illumina data resulted in clustering of soil samples identical to that obtained with Sanger sequence clone library data using different primers. Furthermore, the two methods produced distance matrices with a Mantel correlation of 0.92. Nonfungal sequences comprised less than 0.5% of the soil data set, with most attributable to vascular plants. Our results suggest that high-throughput methods can produce fairly accurate estimates of fungal abundances in complex communities. Further improvements might be achieved through corrections for rRNA copy number and utilization of standardized mock communities.IMPORTANCEFungi play numerous important roles in the environment. Improvements in sequencing methods are providing revolutionary insights into fungal biodiversity, yet accurate estimates of the number of fungal species (i.e., richness) and their relative abundances in an environmental sample (e.g., soil, roots, water, etc.) remain difficult to obtain. We present improved methods for high-throughput Illumina sequencing of the species-diagnostic fungal ribosomal marker gene that improve the accuracy of richness and abundance estimates. The improvements include new PCR primers and library preparation, validation using a known mock community, and bioinformatic parameter tuning.

scholarly journals DNA-Based Herbal Teas’ Authentication: An ITS2 and psbA-trnH Multi-Marker DNA Metabarcoding Approach

Plants ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 2120
Author(s):  
Jessica Frigerio ◽  
Giulia Agostinetto ◽  
Valerio Mezzasalma ◽  
Fabrizio De De Mattia ◽  
Massimo Labra ◽  
...  
Keyword(s):  
Quality Control ◽  
Quantitative Analysis ◽  
Medicinal Plants ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
The Other ◽  
Plant Component ◽  
Identification Rate ◽  
Dna Metabarcoding ◽  
Therapeutic Properties

Medicinal plants have been widely used in traditional medicine due to their therapeutic properties. Although they are mostly used as herbal infusion and tincture, employment as ingredients of food supplements is increasing. However, fraud and adulteration are widespread issues. In our study, we aimed at evaluating DNA metabarcoding as a tool to identify product composition. In order to accomplish this, we analyzed fifteen commercial products with DNA metabarcoding, using two barcode regions: psbA-trnH and ITS2. Results showed that on average, 70% (44–100) of the declared ingredients have been identified. The ITS2 marker appears to identify more species (n = 60) than psbA-trnH (n = 35), with an ingredients’ identification rate of 52% versus 45%, respectively. Some species are identified only by one marker rather than the other. Additionally, in order to evaluate the quantitative ability of high-throughput sequencing (HTS) to compare the plant component to the corresponding assigned sequences, in the laboratory, we created six mock mixtures of plants starting both from biomass and gDNA. Our analysis also supports the application of DNA metabarcoding for a relative quantitative analysis. These results move towards the application of HTS analysis for studying the composition of herbal teas for medicinal plants’ traceability and quality control.

scholarly journals mockrobiota: a Public Resource for Microbiome Bioinformatics Benchmarking

mSystems ◽  
2016 ◽  
Vol 1 (5) ◽  
Author(s):  
Nicholas A. Bokulich ◽  
Jai Ram Rideout ◽  
William G. Mercurio ◽  
Arron Shiffer ◽  
Benjamin Wolfe ◽  
...  
Keyword(s):  
Marker Gene ◽  
Microbial Community Analysis ◽  
Mock Community ◽  
Data Set ◽  
Public Resource ◽  
Source Data ◽  
Community Data ◽  
Dynamic Resource ◽  
And Training ◽  
Mock Communities

ABSTRACT The availability of standard and public mock community data will facilitate ongoing method optimizations, comparisons across studies that share source data, and greater transparency and access and eliminate redundancy. These are also valuable resources for bioinformatics teaching and training. This dynamic resource is intended to expand and evolve to meet the changing needs of the omics community. Mock communities are an important tool for validating, optimizing, and comparing bioinformatics methods for microbial community analysis. We present mockrobiota, a public resource for sharing, validating, and documenting mock community data resources, available at http://caporaso-lab.github.io/mockrobiota/ . The materials contained in mockrobiota include data set and sample metadata, expected composition data (taxonomy or gene annotations or reference sequences for mock community members), and links to raw data (e.g., raw sequence data) for each mock community data set. mockrobiota does not supply physical sample materials directly, but the data set metadata included for each mock community indicate whether physical sample materials are available. At the time of this writing, mockrobiota contains 11 mock community data sets with known species compositions, including bacterial, archaeal, and eukaryotic mock communities, analyzed by high-throughput marker gene sequencing. IMPORTANCE The availability of standard and public mock community data will facilitate ongoing method optimizations, comparisons across studies that share source data, and greater transparency and access and eliminate redundancy. These are also valuable resources for bioinformatics teaching and training. This dynamic resource is intended to expand and evolve to meet the changing needs of the omics community.

scholarly journals Comparison and interpretation of characteristics of Rhizosphere microbiomes of three blueberry varieties

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yan Zhang ◽  
Wei Wang ◽  
Zhangjun Shen ◽  
Jingjing Wang ◽  
Yajun Chen ◽  
...  
Keyword(s):  
Microbial Communities ◽  
High Throughput Sequencing ◽  
Rhizosphere Soil ◽  
Alpha Diversity ◽  
Distribution Patterns ◽  
Soil Samples ◽  
Bulk Soil ◽  
Core Microbiome ◽  
Rhizosphere Microbiome ◽  
Vital Functions

Abstract Background Studies on the rhizosphere microbiome of various plants proved that rhizosphere microbiota carries out various vital functions and can regulate the growth and improve the yield of plants. However, the rhizosphere microbiome of commercial blueberry was only reported by a few studies and remains elusive. Comparison and interpretation of the characteristics of the rhizosphere microbiome of blueberry are critical important to maintain its health. Results In this study, a total of 20 rhizosphere soil samples, including 15 rhizosphere soil samples from three different blueberry varieties and five bulk soil samples, were sequenced with a high-throughput sequencing strategy. Based on these sequencing datasets, we profiled the taxonomical, functional, and phenotypic compositions of rhizosphere microbial communities for three different blueberry varieties and compared our results with a previous study focused on the rhizosphere microbiome of blueberry varieties. Our results demonstrated significant differences in alpha diversity and beta diversity of rhizosphere microbial communities of different blueberry varieties and bulk soil. The distribution patterns of taxonomical, functional, and phenotypic compositions of rhizosphere microbiome differ across the blueberry varieties. The rhizosphere microbial communities of three different blueberry varieties could be distinctly separated, and 28 discriminative biomarkers were selected to distinguish these three blueberry varieties. Core rhizosphere microbiota for blueberry was identified, and it contained 201 OTUs, which were mainly affiliated with Proteobacteria, Actinobacteria, and Acidobacteria. Moreover, the interactions between OTUs of blueberry rhizosphere microbial communities were explored by a co-occurrence network of OTUs from an ecological perspective. Conclusions This pilot study explored the characteristics of blueberry’s rhizosphere microbial community, such as the beneficial microorganisms and core microbiome, and provided an integrative perspective on blueberry’s rhizosphere microbiome, which beneficial to blueberry health and production.

scholarly journals Trophic Selective Pressures Organize the Composition of Endolithic Microbial Communities from Global Deserts

2019 ◽  
Author(s):  
Evan Qu ◽  
Chris Omelon ◽  
Aharon Oren ◽  
Victoria Meslier ◽  
Don A. Cowan ◽  
...  
Keyword(s):  
Microbial Communities ◽  
High Throughput ◽  
Community Assembly ◽  
High Throughput Sequencing ◽  
Regional Scale ◽  
Marker Gene ◽  
Trophic Levels ◽  
Striking Difference ◽  
Climate Conditions ◽  
Endolithic Community

AbstractStudies of microbial biogeography are often convoluted by extremely high diversity and differences in microenvironmental factors such as pH and nutrient availability. Desert endolithic (inside rock) communities are exceptionally simple ecosystems that can serve as a tractable model for investigating long-range biogeographic effects on microbial communities. We conducted a comprehensive survey of endolithic sandstones using high-throughput marker gene sequencing to characterize global patterns of diversity in endolithic microbial communities. We also tested a range of abiotic variables in order to investigate the factors that drive community assembly at various trophic levels. Macroclimate was found to be the primary driver of endolithic community composition, with the most striking difference witnessed between hot and polar deserts. This difference was largely attributable to the specialization of prokaryotic and eukaryotic primary producers to different climate conditions. On a regional scale, microclimate and properties of the rock substrate were found to influence community assembly, although to a lesser degree than global hot versus polar conditions. We found new evidence that the factors driving endolithic community assembly differ between trophic levels. While phototrophic taxa were rigorously selected for among different sites, heterotrophic taxa were more cosmopolitan, suggesting that stochasticity plays a larger role in heterotroph assembly. This study is the first to uncover the global drivers of desert endolithic diversity using high-throughput sequencing. We demonstrate that phototrophs and heterotrophs in the endolithic community assemble under different stochastic and deterministic influences, emphasizing the need for studies of microorganisms in context of their functional niche in the community.

scholarly journals Optimization of 16S amplicon analysis using mock communities: implications for estimating community diversity

2016 ◽  
Author(s):  
Andrew Krohn ◽  
Bo Stevens ◽  
Adam Robbins-Pianka ◽  
Matthew Belus ◽  
Gerard J Allan ◽  
...  
Keyword(s):  
Dna Sequences ◽  
Marker Gene ◽  
Community Diversity ◽  
Sequencing Data ◽  
Mock Community ◽  
Taxonomic Assignment ◽  
Data Set ◽  
Environmental Diversity ◽  
Quality Filtering ◽  
Mock Communities

The diversity of complex microbial communities can be rapidly assessed by high-throughput DNA sequencing of marker gene (e.g., 16S) PCR amplicon pools, often yielding many thousands of DNA sequences per sample. However, analysis of such community amplicon sequencing data requires multiple computational steps which affect the outcome of a final data set. Here we use mock communities to describe the effects of parameter adjustments for raw sequence quality filtering, picking operational taxonomic units (OTUs), taxonomic assignment, and OTU table filtering as implemented in the popular microbial ecology analysis package, QIIME 1.9.1. We demonstrate a workflow optimization based upon this exploration, which we also apply to environmental samples. We found that quality filtering of raw data and filtering of OTU tables had large effects on observed OTU diversity. While all taxonomy assignment programs performed with similar accuracy, an appropriate choice of similarity threshold for defining OTUs depended on the method used for OTU picking. Our “default” analysis in QIIME overestimated mock community OTU diversity by at least a factor of ten. Our optimized analysis correctly characterized mock community taxonomic composition and improved the OTU diversity estimate, reducing overestimation to a factor of about two. Though observed relative abundances of mock community member taxa were approximately correct, most were still represented by multiple OTUs. Low-frequency OTUs conspecific to constituent mock community taxa were characterized by multiple substitution and indel errors and the presence of a low-quality base call resulting in sequence truncation during quality filtering. Low-quality base calls were observed at “G” positions most of the time, and were also associated with a preceding “TTT” trinucleotide motif. Environmental diversity estimates were reduced by about 40% from 2508 to 1533 OTUs when comparing output from the default and optimized workflows. We attribute this reduction in observed diversity to the removal of erroneous sequences from the data set. Our results indicate that both strict quality filtering of raw sequencing data and careful filtering of raw OTU tables are important steps for accurately estimating microbial community diversity.

scholarly journals Starch Degradation by Microbial Communities in Soils from Oldupai Gorge (Tanzania)

2019 ◽  
Author(s):  
Tolutope Akeju ◽  
Peter Dunfield ◽  
Julio Mercader
Keyword(s):  
Microbial Communities ◽  
High Throughput Sequencing ◽  
Fungal Species ◽  
Soil Samples ◽  
Model Organisms ◽  
Starch Degradation ◽  
Soil Conditions ◽  
Soil Microbial ◽  
Specific Species ◽  
Microbial Dna

The taphonomy behind ancient starch preservation is very poorly understood in archaeological contexts. This understanding could be aided by biogeochemical experimentation in controlled laboratory environments to isolate degradation pathways in soils, and how this degradation is affected by biotic and abiotic variables. The aims of this project were to:1) Identify and characterize bacterial and fungal species responsible for the degradation of starch in Tanzanian soils2) Determine how factors such as the starch source, soil water, and soil aeration affect the activity of these microbes3) Observe the alterations of starch granules inflicted by degradation by different microbial communities. Field and laboratory studies were designed to achieve these objectives:In the field, bulk soil samples (not adjacent to plant roots/tubers) and tubersphere soil samples (attached to starchy plant tubers) were collected for analysis of microbial communities via high-throughput sequencing of soil microbial DNA. Laboratory analysis of these samples is ongoing, but initial results suggest that particular starch-degrading microbes associate with particular starchy tubers. Secondly, controlled laboratory microcosms of soils amended with various starch types were incubated under different conditions. The microbial communities degrading the starch were followed over time via DNA sequencing and the starch taphonomy observed microscopically. These studies have shown that hardy, spore-forming bacteria of the phylum Firmicutes dominate starch-degrading microbial communities in the Tanzanian soils, but that the specific species change depending on experimental variables. The soil conditions and the source of the starch dramatically affected both the degradation rate and the specific microbial species involved. These findings suggest that starch degradation and taphonomy may be site-specific, that certain starches may be more prone to preservation than others may, and that starch-degradation studies using model organisms may not always be representative of the field conditions.

Analysis of the structure of bacterial and fungal communities in disease suppressive and disease conducive tobacco-planting soils in China

Soil Research ◽  
2020 ◽  
Vol 58 (1) ◽  
pp. 35
Author(s):  
Lin Gao ◽  
Rui Wang ◽  
Jiaming Gao ◽  
Fangming Li ◽  
Guanghua Huang ◽  
...  
Keyword(s):  
Microbial Communities ◽  
High Throughput Sequencing ◽  
Soil Samples ◽  
Fungal Communities ◽  
Sequencing Technology ◽  
Operational Taxonomic Units ◽  
Tobacco Cultivation ◽  
Bacteria And Fungi ◽  
Disease Suppressive Soil ◽  
Conducive Soil

To clarify the differences between microbial communities resident in disease suppressive soil (DSS) and disease conducive soil (DCS) in tobacco cultivation, representative soil samples were collected from tobacco plantations in Shengjiaba, China, and the structure and diversity of the resident bacterial and fungal communities were analysed using high-throughput sequencing technology. Our results showed a greater number of operational taxonomic units associated with bacteria and fungi in DSS than in DCS. At the phylum level, abundances of Chloroflexi, Saccharibacteria, Firmicutes, and Planctomycetes in DSS were lower than in DCS, but abundance of Gemmatimonadetes was significantly higher. Abundances of Zygomycota and Chytridiomycota were higher in DSS than DCS, but abundance of Rozellomycota was significantly lower. At the genus level, abundances of 18 bacterial and nine fungal genera varied significantly between DSS and DCS. Relative abundances of Acidothermus, Microbacterium, Curtobacterium, and Colletotrichum were higher in DCS than DSS. The Shannon and Chao1 indices of DSS microbial communities were higher than those of DCS communities. High microbial diversity reduces the incidence of soil-borne diseases in tobacco plantations and promotes the formation of DSSs.

scholarly journals Protistan and fungal diversity in soils and freshwater lakes are substantially different

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
G. Sieber ◽  
D. Beisser ◽  
C. Bock ◽  
J. Boenigk
Keyword(s):  
Microbial Communities ◽  
High Throughput Sequencing ◽  
Soil Samples ◽  
Habitat Characteristics ◽  
Community Similarity ◽  
Habitat Types ◽  
Illumina Hiseq ◽  
Diversity Pattern ◽  
Relative Contribution ◽  
Catchment Areas

AbstractFreshwater and soil habitats hold rich microbial communities. Here we address commonalities and differences between both habitat types. While freshwater and soil habitats differ considerably in habitat characteristics organismic exchange may be high and microbial communities may even be inoculated by organisms from the respective other habitat. We analyze diversity pattern and the overlap of taxa of eukaryotic microbial communities in freshwater and soil based on Illumina HiSeq high-throughput sequencing of the amplicon V9 diversity. We analyzed corresponding freshwater and soil samples from 30 locations, i.e. samples from different lakes across Germany and soil samples from the respective catchment areas. Aside from principle differences in the community composition of soils and freshwater, in particular with respect to the relative contribution of fungi and algae, soil habitats have a higher richness. Nevertheless, community similarity between different soil sites is considerably lower as compared to the similarity between different freshwater sites. We show that the overlap of organisms co-occurring in freshwater and soil habitats is surprisingly low. Even though closely related taxa occur in both habitats distinct OTUs were mostly habitat–specific and most OTUs occur exclusively in either soil or freshwater. The distribution pattern of the few co-occurring lineages indicates that even most of these are presumably rather habitat-specific. Their presence in both habitat types seems to be based on a stochastic drift of particularly abundant but habitat-specific taxa rather than on established populations in both types of habitats.

scholarly journals Optimization of 16S amplicon analysis using mock communities: implications for estimating community diversity

2016 ◽  
Author(s):  
Andrew Krohn ◽  
Bo Stevens ◽  
Adam Robbins-Pianka ◽  
Matthew Belus ◽  
Gerard J Allan ◽  
...  
Keyword(s):  
Dna Sequences ◽  
Marker Gene ◽  
Community Diversity ◽  
Sequencing Data ◽  
Mock Community ◽  
Taxonomic Assignment ◽  
Data Set ◽  
Environmental Diversity ◽  
Quality Filtering ◽  
Mock Communities

The diversity of complex microbial communities can be rapidly assessed by high-throughput DNA sequencing of marker gene (e.g., 16S) PCR amplicon pools, often yielding many thousands of DNA sequences per sample. However, analysis of such community amplicon sequencing data requires multiple computational steps which affect the outcome of a final data set. Here we use mock communities to describe the effects of parameter adjustments for raw sequence quality filtering, picking operational taxonomic units (OTUs), taxonomic assignment, and OTU table filtering as implemented in the popular microbial ecology analysis package, QIIME 1.9.1. We demonstrate a workflow optimization based upon this exploration, which we also apply to environmental samples. We found that quality filtering of raw data and filtering of OTU tables had large effects on observed OTU diversity. While all taxonomy assignment programs performed with similar accuracy, an appropriate choice of similarity threshold for defining OTUs depended on the method used for OTU picking. Our “default” analysis in QIIME overestimated mock community OTU diversity by at least a factor of ten. Our optimized analysis correctly characterized mock community taxonomic composition and improved the OTU diversity estimate, reducing overestimation to a factor of about two. Though observed relative abundances of mock community member taxa were approximately correct, most were still represented by multiple OTUs. Low-frequency OTUs conspecific to constituent mock community taxa were characterized by multiple substitution and indel errors and the presence of a low-quality base call resulting in sequence truncation during quality filtering. Low-quality base calls were observed at “G” positions most of the time, and were also associated with a preceding “TTT” trinucleotide motif. Environmental diversity estimates were reduced by about 40% from 2508 to 1533 OTUs when comparing output from the default and optimized workflows. We attribute this reduction in observed diversity to the removal of erroneous sequences from the data set. Our results indicate that both strict quality filtering of raw sequencing data and careful filtering of raw OTU tables are important steps for accurately estimating microbial community diversity.

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