scholarly journals CaptureSeq: Hybridization-based enrichment of cpn60 gene fragments reveals the community structures of synthetic and natural microbial ecosystems

2018 ◽  
Author(s):  
Matthew G. Links ◽  
Tim J. Dumonceaux ◽  
Luke McCarthy ◽  
Sean M. Hemmingsen ◽  
Edward Topp ◽  
...  
Keyword(s):  
Microbial Community ◽  
Microbial Communities ◽  
Shotgun Sequencing ◽  
Natural Ecosystems ◽  
Gene Markers ◽  
Microbiome Composition ◽  
Microbial Profile ◽  
Domains Of Life ◽  
Metagenome Sequencing ◽  
Pcr Targeting

AbstractBackgroundMolecular profiling of complex microbial communities has become the basis for examining the relationship between the microbiome composition, structure and metabolic functions of those communities. Microbial community structure can be partially assessed with universal PCR targeting taxonomic or functional gene markers. Increasingly, shotgun metagenomic DNA sequencing is providing more quantitative insight into microbiomes. However, both amplicon-based and shotgun sequencing approaches have shortcomings that limit the ability to study microbiome dynamics.MethodsWe present a novel, amplicon-free, hybridization-based method (CaptureSeq) for profiling complex microbial communities using probes based on the chaperonin-60 gene. Molecular profiles of a commercially available synthetic microbial community standard were compared using CaptureSeq, whole metagenome sequencing, and 16S universal target amplification. Profiles were also generated for natural ecosystems including antibiotic-amended soils, manure storage tanks, and an agricultural reservoir.ResultsThe CaptureSeq method generated a microbial profile that encompassed all of the bacteria and eukaryotes in the panel with greater reproducibility and more accurate representation of high G/C content microorganisms compared to 16S amplification. In the natural ecosystems, CaptureSeq provided a much greater depth of coverage and sensitivity of detection compared to shotgun sequencing without prior selection. The resulting community profiles provided quantitatively reliable information about all three Domains of life (Bacteria, Archaea, and Eukarya) in the different ecosystems. The applications of CaptureSeq will facilitate accurate studies of host-microbiome interactions for environmental, crop, animal and human health.

scholarly journals CaptureSeq: Hybridization-Based Enrichment of cpn60 Gene Fragments Reveals the Community Structures of Synthetic and Natural Microbial Ecosystems

2021 ◽  
Vol 9 (4) ◽  
pp. 816
Author(s):  
Matthew G. Links ◽  
Tim J. Dumonceaux ◽  
E. Luke McCarthy ◽  
Sean M. Hemmingsen ◽  
Edward Topp ◽  
...  
Keyword(s):  
Microbial Community ◽  
Microbial Communities ◽  
Dna Sequences ◽  
Pcr Amplification ◽  
Shotgun Sequencing ◽  
Natural Ecosystems ◽  
Gene Markers ◽  
Microbial Profile ◽  
Microbial Ecosystems ◽  
Pcr Targeting

Background. The molecular profiling of complex microbial communities has become the basis for examining the relationship between the microbiome composition, structure and metabolic functions of those communities. Microbial community structure can be partially assessed with “universal” PCR targeting taxonomic or functional gene markers. Increasingly, shotgun metagenomic DNA sequencing is providing more quantitative insight into microbiomes. However, both amplicon-based and shotgun sequencing approaches have shortcomings that limit the ability to study microbiome dynamics. Methods. We present a novel, amplicon-free, hybridization-based method (CaptureSeq) for profiling complex microbial communities using probes based on the chaperonin-60 gene. Molecular profiles of a commercially available synthetic microbial community standard were compared using CaptureSeq, whole metagenome sequencing, and 16S universal target amplification. Profiles were also generated for natural ecosystems including antibiotic-amended soils, manure storage tanks, and an agricultural reservoir. Results. The CaptureSeq method generated a microbial profile that encompassed all of the bacteria and eukaryotes in the panel with greater reproducibility and more accurate representation of high G/C content microorganisms compared to 16S amplification. In the natural ecosystems, CaptureSeq provided a much greater depth of coverage and sensitivity of detection compared to shotgun sequencing without prior selection. The resulting community profiles provided quantitatively reliable information about all three domains of life (Bacteria, Archaea, and Eukarya) in the different ecosystems. The applications of CaptureSeq will facilitate accurate studies of host-microbiome interactions for environmental, crop, animal and human health. Conclusions: cpn60-based hybridization enriched for taxonomically informative DNA sequences from complex mixtures. In synthetic and natural microbial ecosystems, CaptureSeq provided sequences from prokaryotes and eukaryotes simultaneously, with quantitatively reliable read abundances. CaptureSeq provides an alternative to PCR amplification of taxonomic markers with deep community coverage while minimizing amplification biases.

scholarly journals Reduced metagenome sequencing for strain-resolution taxonomic profiles

Microbiome ◽  
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Lars Snipen ◽  
Inga-Leena Angell ◽  
Torbjørn Rognes ◽  
Knut Rudi
Keyword(s):  
Microbial Community ◽  
Microbial Community Composition ◽  
Amplicon Sequencing ◽  
Good Alternative ◽  
Shotgun Sequencing ◽  
Least Square ◽  
Full Potential ◽  
Shotgun Metagenomics ◽  
Metagenome Sequencing ◽  
Reference Genomes

Abstract Background Studies of shifts in microbial community composition has many applications. For studies at species or subspecies levels, the 16S amplicon sequencing lacks resolution and is often replaced by full shotgun sequencing. Due to higher costs, this restricts the number of samples sequenced. As an alternative to a full shotgun sequencing we have investigated the use of Reduced Metagenome Sequencing (RMS) to estimate the composition of a microbial community. This involves the use of double-digested restriction-associated DNA sequencing, which means only a smaller fraction of the genomes are sequenced. The read sets obtained by this approach have properties different from both amplicon and shotgun data, and analysis pipelines for both can either not be used at all or not explore the full potential of RMS data. Results We suggest a procedure for analyzing such data, based on fragment clustering and the use of a constrained ordinary least square de-convolution for estimating the relative abundance of all community members. Mock community datasets show the potential to clearly separate strains even when the 16S is 100% identical, and genome-wide differences is < 0.02, indicating RMS has a very high resolution. From a simulation study, we compare RMS to shotgun sequencing and show that we get improved abundance estimates when the community has many very closely related genomes. From a real dataset of infant guts, we show that RMS is capable of detecting a strain diversity gradient for Escherichia coli across time. Conclusion We find that RMS is a good alternative to either metabarcoding or shotgun sequencing when it comes to resolving microbial communities at the strain level. Like shotgun metagenomics, it requires a good database of reference genomes and is well suited for studies of the human gut or other communities where many reference genomes exist. A data analysis pipeline is offered, as an R package at https://github.com/larssnip/microRMS.

scholarly journals Combining whole genome shotgun sequencing and rDNA amplicon analyses to improve detection of microbe-microbe interaction networks in plant leaves

2019 ◽  
Author(s):  
Julian Regalado ◽  
Derek S. Lundberg ◽  
Oliver Deusch ◽  
Sonja Kersten ◽  
Talia Karasov ◽  
...  
Keyword(s):  
16S Rdna ◽  
High Throughput Sequencing ◽  
Cost Effective ◽  
Amplicon Sequencing ◽  
Low Complexity ◽  
Shotgun Sequencing ◽  
Wild Plants ◽  
Hybrid Strategy ◽  
Domains Of Life ◽  
Metagenome Sequencing

AbstractMicroorganisms from all domains of life establish associations with plants. Although some harm the plant, others antagonize pathogens or prime the plant immune system, acquire nutrients, tune plant hormone levels, or perform additional services. Most culture-independent plant microbiome research has focused on amplicon sequencing of 16S rDNA and/or the internal transcribed spacer (ITS) of rDNA loci, but the decreasing cost of high-throughput sequencing has made shotgun metagenome sequencing increasingly accessible. Here, we describe shotgun sequencing of 275 wild Arabidopsis thaliana leaf microbiomes from southwest Germany, with additional bacterial 16S rDNA and eukaryotic ITS1 amplicon data from 176 of these samples. The shotgun data were dominated by bacterial sequences, with eukaryotes contributing only a minority of reads. For shotgun and amplicon data, microbial membership showed weak associations with both site of origin and plant genotype, both of which were highly confounded in this dataset. There was large variation among microbiomes, with one extreme comprising samples of low complexity and a high load of microorganisms typical of infected plants, and the other extreme being samples of high complexity and a low microbial load. We use the metagenome data, which captures the ratio of bacterial to plant DNA in leaves of wild plants, to scale the 16S rDNA amplicon data such that they reflect absolute bacterial abundance. We show that this cost-effective hybrid strategy overcomes compositionality problems in amplicon data and leads to fundamentally different conclusions about microbiome community assembly.

scholarly journals A step-by-step sequence-based analysis of virome enrichment protocol for freshwater and sediment samples

2020 ◽  
Author(s):  
Federica Pinto ◽  
Moreno Zolfo ◽  
Francesco Beghini ◽  
Federica Armanini ◽  
Francesco Asnicar ◽  
...  
Keyword(s):  
Microbial Community ◽  
Microbial Communities ◽  
Microbial Community Composition ◽  
Genetic Material ◽  
Amplicon Sequencing ◽  
Sample Type ◽  
Natural Ecosystems ◽  
Sediment Samples ◽  
Water And Sediment ◽  
Water And Sediment Samples

AbstractCultivation-free metagenomic analysis afforded unprecedented details on the diversity, structure and potential functions of microbial communities in different environments. When employed to study the viral fraction of the community that is recalcitrant to cultivation, metagenomics can shed light into the diversity of viruses and their role in natural ecosystems. However, despite the increasing interest in virome metagenomics, methodological issues still hinder the proper interpretation and comparison of results across studies. Virome enrichment experimental protocols are key multi-step processes needed for separating and concentrating the viral fraction from the whole microbial community prior to sequencing. However, there is little information on their efficiency and their potential biases. To fill this gap, we used metagenomic and amplicon sequencing to examine the microbial community composition through the serial filtration and concentration steps commonly used to produce viral-enriched metagenomes. The analyses were performed on water and sediment samples from an Alpine lake. We found that, although the diversity of the retained microbial communities declined progressively during the serial filtration, the final viral fraction contained a large proportion (from 10% to 40%) of non-viral taxa, and that the efficacy of filtration showed biases based on taxonomy. Our results quantified the amount of bacterial genetic material in viromes and highlighted the influence of sample type on the enrichment efficacy. Moreover, since viral-enriched samples contained a significant portion of microbial taxa, computational sequence analysis should account for such biases in the downstream interpretation pipeline.ImportanceFiltration is a commonly used method to enrich viral particles in environmental samples. However, there is little information on its efficiency and potential biases on the final result. Using a sequence-based analysis on water and sediment samples, we found that filtration efficacy is dependent on sample type and that the final virome contained a large proportion of non-viral taxa. Our finding stressed the importance of downstream analysis to avoid biased interpretation of data.

scholarly journals Reduced Metagenome Sequencing for strain-resolution taxonomic profiles

2021 ◽  
Author(s):  
Lars Snipen ◽  
Inga-Leena Angell ◽  
Torbjørn Rognes ◽  
Knut Rudi
Keyword(s):  
Microbial Community ◽  
Microbial Community Composition ◽  
Real Data ◽  
Shotgun Sequencing ◽  
Least Square ◽  
Full Potential ◽  
Data Set ◽  
Shotgun Metagenomics ◽  
Metagenome Sequencing ◽  
Reference Genomes

Abstract BackgroundStudies of shifts in microbial community composition has many applications. For studies at species or subspecies levels, the 16S amplicon sequencing lacks resolution, and is often replaced by full shotgun sequencing. Due to higher costs, this restricts the number of samples sequenced. As an alternative to a full shotgun sequencing we have investigated the use of Reduced Metagenome Sequencing (RMS) to estimate the composition of a microbial community. This involves the use of double-digested restriction associated DNA sequencing, which means only a smaller fraction of the genomes are sequenced. The read sets obtained by this approach have properties different from both amplicon and shotgun data, and analysis pipelines for both can either not be used at all or do not explore the full potential of RMS data.ResultsWe suggest a procedure for analyzing such data, based on fragment clustering and the use of a constrained ordinary least square de-convolution for estimating the relative abundance of all community members. Mock-community data sets shows the potential to clearly separate between strains even when the 16S is 100% identical and genome-wide differences is <0.02, indicating RMS has a very high resolution. From a simulation study we compare RMS to shotgun sequencing and show that we get improved abundance estimates when the community has many very closely related genomes. From a real data set of infants guts we show that RMS is capable of detecting a strain-diversity gradient for Escherichia coli across time.ConclusionWe find that RMS is a good alternative to either metabarcoding or shotgun sequencing when it comes to resolving microbial communities at the strain-level. Like shotgun metagenomics, it requires a good database of reference genomes, and is well suited for studies of the human gut or other communities where many reference genomes exist. A data analysis pipeline is offered, as an R package at https://github.com/larssnip/microRMS.

scholarly journals A coexistence theory in microbial communities

2018 ◽  
Vol 5 (9) ◽  
pp. 180476 ◽  
Author(s):  
Marina Dohi ◽  
Akihiko Mougi
Keyword(s):  
Microbial Community ◽  
Equilibrium State ◽  
Microbial Communities ◽  
Critical Role ◽  
Abundance Ratio ◽  
The Other ◽  
Natural Ecosystems ◽  
Trade Off ◽  
Coexistence Theory ◽  
Different Types

Microbes are widespread in natural ecosystems where they create complex communities. Understanding the functions and dynamics of such microbial communities is a very important theme not only for ecology but also for humankind because microbes can play major roles in our health. Yet, it remains unclear how such complex ecosystems are maintained. Here, we present a simple theory on the dynamics of a microbial community. Bacteria preferring a particular pH in their environment indirectly inhibit the growth of the other types of bacteria by changing the pH to their optimum value. This pH-driven interaction always causes a state of bistability involving different types of bacteria that can be more or less abundant. Furthermore, a moderate abundance ratio of different types of bacteria can confer enhanced resilience to a specific equilibrium state, particularly when a trade-off relationship exists between growth and the ability of bacteria to change the pH of their environment. These results suggest that the balance of the composition of microbiota plays a critical role in maintaining microbial communities.

scholarly journals Reduced Metagenome Sequencing for strain-resolution taxonomic proles

2020 ◽  
Author(s):  
Lars Snipen ◽  
Inga-Leena Angell ◽  
Torbjørn Rognes ◽  
Knut Rudi
Keyword(s):  
Microbial Community ◽  
Microbial Community Composition ◽  
Real Data ◽  
Shotgun Sequencing ◽  
Least Square ◽  
Full Potential ◽  
Data Set ◽  
Shotgun Metagenomics ◽  
Metagenome Sequencing ◽  
Reference Genomes

Abstract Background: Studies of shifts in microbial community composition has many applications. For studies at species or subspecies levels, the 16S amplicon sequencing lacks resolution, and is often replaced by full shotgun sequencing. Due to higher costs, this restricts the number of samples sequenced. As an alternative to a full shotgun sequencing we have investigated the use of Reduced Metagenome Sequencing (RMS) to estimate the composition of a microbial community. This involves the use of double-digested restriction associated DNA sequencing, which means only a smaller fraction of the genomes are sequenced. The read sets obtained by this approach have properties different from both amplicon and shotgun data, and analysis pipelines for both can either not be used at all or do not explore the full potential of RMS data.Results: We suggest a procedure for analyzing such data, based on fragment clustering and the use of a constrained ordinary least square de-convolution for estimating the relative abundance of all community members. Mock-community data sets shows the potential to clearly separate between strains even when the 16S is 100% identical and genome-wide dierences is < 0:02, indicating RMS has a very high resolution. From a simulation study we compare RMS to shotgun sequencing and show that we get improved abundance estimates when the community has many very closely related genomes. From a real data set of infants guts we show that RMS is capable of detecting a strain-diversity gradient for Escherichia coli across time.Conclusion: We find that RMS is a good alternative to either metabarcoding or shotgun sequencing when it comes to resolving microbial communities at the strain-level. Like shotgun metagenomics, it requires a good database of reference genomes, and is well suited for studies of the human gut or other communities where many reference genomes exist. A data analysis pipeline is offered, as an R package at https://github.com/larssnip/microRMS.

scholarly journals Taxonomic and functional analyses of intact microbial communities thriving in extreme, astrobiology-relevant, anoxic sites

Microbiome ◽  
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Alexandra Kristin Bashir ◽  
Lisa Wink ◽  
Stefanie Duller ◽  
Petra Schwendner ◽  
Charles Cockell ◽  
...  
Keyword(s):  
Microbial Community ◽  
Microbial Communities ◽  
Extreme Environments ◽  
Acidic Lake ◽  
Intact Cells ◽  
Core Microbiome ◽  
Anoxic Environments ◽  
Microbiome Profile ◽  
Metagenome Sequencing ◽  
Physical And Chemical

Abstract Background Extreme terrestrial, analogue environments are widely used models to study the limits of life and to infer habitability of extraterrestrial settings. In contrast to Earth’s ecosystems, potential extraterrestrial biotopes are usually characterized by a lack of oxygen. Methods In the MASE project (Mars Analogues for Space Exploration), we selected representative anoxic analogue environments (permafrost, salt-mine, acidic lake and river, sulfur springs) for the comprehensive analysis of their microbial communities. We assessed the microbiome profile of intact cells by propidium monoazide-based amplicon and shotgun metagenome sequencing, supplemented with an extensive cultivation effort. Results The information retrieved from microbiome analyses on the intact microbial community thriving in the MASE sites, together with the isolation of 31 model microorganisms and successful binning of 15 high-quality genomes allowed us to observe principle pathways, which pinpoint specific microbial functions in the MASE sites compared to moderate environments. The microorganisms were characterized by an impressive machinery to withstand physical and chemical pressures. All levels of our analyses revealed the strong and omnipresent dependency of the microbial communities on complex organic matter. Moreover, we identified an extremotolerant cosmopolitan group of 34 poly-extremophiles thriving in all sites. Conclusions Our results reveal the presence of a core microbiome and microbial taxonomic similarities between saline and acidic anoxic environments. Our work further emphasizes the importance of the environmental, terrestrial parameters for the functionality of a microbial community, but also reveals a high proportion of living microorganisms in extreme environments with a high adaptation potential within habitability borders.

scholarly journals Microbial community-level features linked to divergent carbon flows during early litter decomposition in a constant environment

2019 ◽  
Author(s):  
Renee Johansen ◽  
Michaeline Albright ◽  
Deanna Lopez ◽  
La Verne Gallegos-Graves ◽  
Andreas Runde ◽  
...  
Keyword(s):  
Microbial Community ◽  
Microbial Communities ◽  
Litter Decomposition ◽  
Plant Litter ◽  
Carbon Flow ◽  
Community Level ◽  
Natural Ecosystems ◽  
Long Term Storage ◽  
Plant Litter Decomposition ◽  
Underlying Mechanisms

AbstractDuring plant litter decomposition in soils, carbon has two general fates: return to the atmosphere via microbial respiration or transport into soil where long-term storage may occur. Discovering microbial community features that drive carbon fate from litter decomposition may improve modeling and management of soil carbon. This concept assumes there are features (or underlying processes) that are widespread among disparate communities, and therefore amenable to modeling. We tested this assumption using an epidemiological approach in which two contrasting patterns of carbon flow in laboratory microcosms were delineated as functional states and diverse microbial communities representing each state were compared to discover shared features linked to carbon fate. Microbial communities from 206 soil samples from the southwestern United States were inoculated on plant litter in microcosms, and carbon flow was measured as cumulative carbon dioxide (CO2) and dissolved organic carbon (DOC) after 44 days. Carbon flow varied widely among the microcosms, with a 2-fold range in cumulative CO2efflux and a 5-fold range in DOC quantity. Bacteria, not fungi, were the strongest drivers of DOC variation. The most significant community-level feature linked to DOC abundance was bacterial richness—the same feature linked to carbon fate in human-gut microbiome studies. This proof-of-principle study under controlled conditions suggests common features driving carbon flow in disparate microbial communities can be identified, motivating further exploration of underlying mechanisms that may influence carbon fate in natural ecosystems.

scholarly journals Reduced Metagenome Sequencing for strain-resolution taxonomic proles

2020 ◽  
Author(s):  
Lars Snipen ◽  
Inga-Leena Angell ◽  
Torbjørn Rognes ◽  
Knut Rudi
Keyword(s):  
Microbial Community ◽  
Microbial Community Composition ◽  
Real Data ◽  
Shotgun Sequencing ◽  
Least Square ◽  
Full Potential ◽  
Data Set ◽  
Shotgun Metagenomics ◽  
Metagenome Sequencing ◽  
Reference Genomes

Abstract Background: Studies of shifts in microbial community composition has many applications. For studies at species or subspecies levels, the 16S amplicon sequencing lacks resolution, and is often replaced by full shotgun sequencing. Due to higher costs, this restricts the number of samples sequenced. As an alternative to a full shotgun sequencing we have investigated the use of Reduced Metagenome Sequencing (RMS) to estimate the composition of a microbial community. This involves the use of double-digested restriction associated DNA sequencing, which means only a smaller fraction of the genomes are sequenced. The read sets obtained by this approach have properties different from both amplicon and shotgun data, and analysis pipelines for both can either not be used at all or do not explore the full potential of RMS data. Results: We suggest a procedure for analyzing such data, based on fragment clustering and the use of a constrained ordinary least square de-convolution for estimating the relative abundance of all community members. Mock-community data sets shows the potential to clearly separate between strains even when the 16S is 100% identical and genome-wide dierences is < 0:02, indicating RMS has a very high resolution. From a simulation study we compare RMS to shotgun sequencing and show that we get improved abundance estimates when the community has many very closely related genomes. From a real data set of infants guts we show that RMS is capable of detecting a strain-diversity gradient for Escherichia coli across time. Conclusion: We find that RMS is a good alternative to either metabarcoding or shotgun sequencing when it comes to resolving microbial communities at the strain-level. Like shotgun metagenomics, it requires a good database of reference genomes, and is well suited for studies of the human gut or other communities where many reference genomes exist. A data analysis pipeline is offered, as an R package at https://github.com/larssnip/microRMS. Keywords: metagenome; strains; ddRADseq

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