scholarly journals Combined Stochastic and Deterministic Processes Drive Community Assembly of Anaerobic Microbiomes During Granule Flotation

2021 ◽  
Vol 12 ◽  
Author(s):  
Anna Christine Trego ◽  
Paul G. McAteer ◽  
Corine Nzeteu ◽  
Therese Mahony ◽  
Florence Abram ◽  
...  
Keyword(s):  
Community Assembly ◽  
Null Model ◽  
Amplicon Sequencing ◽  
Dairy Wastewater ◽  
Rrna Gene ◽  
Primary Mechanism ◽  
Process Failure ◽  
Deterministic Processes ◽  
Process Disturbances ◽  
Model Approach

Advances in null-model approaches have resulted in a deeper understanding of community assembly mechanisms for a variety of complex microbiomes. One under-explored application is assembly of communities from the built-environment, especially during process disturbances. Anaerobic digestion for biological wastewater treatment is often underpinned by retaining millions of active granular biofilm aggregates. Flotation of granules is a major problem, resulting in process failure. Anaerobic aggregates were sampled from three identical bioreactors treating dairy wastewater. Microbiome structure was analysed using qPCR and 16S rRNA gene amplicon sequencing from DNA and cDNA. A comprehensive null-model approach quantified assembly mechanisms of floating and settled communities. Significant differences in diversity were observed between floating and settled granules, in particular, we highlight the changing abundances of Methanosaeta and Lactococcus. Both stochastic and deterministic processes were important for community assembly. Homogeneous selection was the primary mechanism for all categories, but dispersal processes also contributed. The lottery model was used to identify clade-level competition driving community assembly. Lottery “winners” were identified with different winners between floating and settled groups. Some groups changed their winner status when flotation occurred. Spirochaetaceae, for example, was only a winner in settled biomass (cDNA-level) and lost its winner status during flotation. Alternatively, Arcobacter butzerli gained winner status during flotation. This analysis provides a deeper understanding of changes that occur during process instabilities and identified groups which may be washed out—an important consideration for process control.

scholarly journals Hill-based dissimilarity indices and null models for analysis of microbial community assembly

2020 ◽  
Author(s):  
Oskar Modin ◽  
Raquel Liébana ◽  
Soroush Sabeh-Alam ◽  
Britt-Marie Wilén ◽  
Carolina Suarez ◽  
...  
Keyword(s):  
Microbial Community ◽  
Relative Abundance ◽  
Community Assembly ◽  
Null Model ◽  
Amplicon Sequencing ◽  
Marker Genes ◽  
Rrna Gene ◽  
Data Set ◽  
Microbial Community Assembly ◽  
The Impact

Abstract Background: High-throughput amplicon sequencing of marker genes, such as the 16S rRNA gene in Bacteria and Archaea, provides a wealth of information about the composition of microbial communities. To quantify differences between samples and draw conclusions about factors affecting community assembly, dissimilarity indices are typically used. However, results are subject to several biases and data interpretation can be challenging. The Jaccard and Bray-Curtis indices, which are often used to quantify taxonomic dissimilarity, are not necessarily the most logical choices. Instead, we argue that Hill-based indices, which make it possible to systematically investigate the impact of relative abundance on dissimilarity, should be used for robust analysis of data. In combination with a null model, mechanisms of microbial community assembly can be analyzed. Here, we also introduce a new software, qdiv, which enables rapid calculations of Hill-based dissimilarity indices in combination with null models.Results: Using amplicon sequencing data from two experimental systems, aerobic granular sludge (AGS) reactors and microbial fuel cells (MFC), we show that the choices of bioinformatics pipeline and dissimilarity index can have considerable impacts on results and conclusions. Analysis of the AGS data set showed that results are sensitive to bioinformatics choices when dissimilarities between sample groups are compared with incidence-based indices. Analysis of the MFC data set with a combination of Hill-based indices and a null model revealed that random dispersal could explain the distribution of both rare and highly abundant taxa within a glucose-fed MFC whereas the distribution of taxa of intermediate relative abundance was governed by heterogeneous selection.Conclusions: Hill-based indices provides a rational framework for analysis of dissimilarity between microbial community samples. In combination with a null model, the effects of deterministic and stochastic factors on taxa of low-, intermediate-, and high relative abundance during microbial community assembly can be systematically investigated. Calculations of Hill-based dissimilarity indices in combination with a null model can be done in qdiv, which is freely available as a Python package (https://github.com/omvatten/qdiv).

scholarly journals Hill-based Dissimilarity Indices and Null Models for Analysis of Microbial Community Assembly

2020 ◽  
Author(s):  
Oskar Modin ◽  
Raquel Liebana ◽  
Soroush Saheb-Alam ◽  
Britt-Marie Wilén ◽  
Carolina Suarez ◽  
...  
Keyword(s):  
Microbial Community ◽  
Microbial Communities ◽  
Community Assembly ◽  
Null Model ◽  
Amplicon Sequencing ◽  
Null Models ◽  
Marker Genes ◽  
Experimental Systems ◽  
Microbial Community Assembly ◽  
The Impact

Abstract Background: High-throughput amplicon sequencing of marker genes, such as the 16S rRNA gene in Bacteria and Archaea, provides a wealth of information about the composition of microbial communities. To quantify differences between samples and draw conclusions about factors affecting community assembly, dissimilarity indices are typically used. However, results are subject to several biases and data interpretation can be challenging. The Jaccard and Bray-Curtis indices, which are often used to quantify taxonomic dissimilarity, are not necessarily the most logical choices. Instead, we argue that Hill-based indices, which make it possible to systematically investigate the impact of relative abundance on dissimilarity, should be used for robust analysis of data. In combination with a null model, mechanisms of microbial community assembly can be analyzed. Here, we also introduce a new software, qdiv, which enables rapid calculations of Hill-based dissimilarity indices in combination with null models.Results: Using amplicon sequencing data from two experimental systems, aerobic granular sludge (AGS) reactors and microbial fuel cells (MFC), we show that the choice of dissimilarity index can have considerable impact on results and conclusions. High dissimilarity between replicates because of random sampling effects make incidence-based indices less suited for identifying differences between groups of samples. Determining a consensus table based on count tables generated with different bioinformatic pipelines reduced the number of low-abundant, potentially spurious amplicon sequence variants (ASVs) in the data sets, which led to lower dissimilarity between replicates. Analysis with a combination of Hill-based indices and a null model allowed us to show that different ecological mechanisms acted on different fractions of the microbial communities in the experimental systems.Conclusions: Hill-based indices provide a rational framework for analysis of dissimilarity between microbial community samples. In combination with a null model, the effects of deterministic and stochastic community assembly factors on taxa of different relative abundances can be systematically investigated. Calculations of Hill-based dissimilarity indices in combination with a null model can be done in qdiv, which is freely available as a Python package (https://github.com/omvatten/qdiv). In qdiv, a consensus table can also be determined from several count tables generated with different bioinformatic pipelines.

scholarly journals Using null models to compare bacterial and microeukaryotic metacommunity assembly under shifting environmental conditions

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Máté Vass ◽  
Anna J. Székely ◽  
Eva S. Lindström ◽  
Silke Langenheder
Keyword(s):  
Community Assembly ◽  
Environmental Conditions ◽  
Null Model ◽  
Temporal Variations ◽  
18S Rrna Gene ◽  
Rrna Gene ◽  
Historical Contingency ◽  
Selection Processes ◽  
Metacommunity Structure ◽  
Microbial Groups

AbstractTemporal variations in microbial metacommunity structure and assembly processes in response to shifts in environmental conditions are poorly understood. Hence, we conducted a temporal field study by sampling rock pools in four-day intervals during a 5-week period that included strong changes in environmental conditions due to intensive rain. We characterized bacterial and microeukaryote communities by 16S and 18S rRNA gene sequencing, respectively. Using a suite of null model approaches (elements of metacommunity structure, Raup-Crick beta-diversity and quantitative process estimates) to assess dynamics in community assembly, we found that strong changes in environmental conditions induced small but significant temporal changes in assembly processes and triggered different responses in bacterial and microeukaryotic metacommunities, promoting distinct selection processes. Incidence-based approaches showed that the assemblies of both communities were mainly governed by stochastic processes. In contrast, abundance-based methods indicated the dominance of historical contingency and unmeasured factors in the case of bacteria and microeukaryotes, respectively. We distinguished these processes from dispersal-related processes using additional tests. Regardless of the applied null model, our study highlights that community assembly processes are not static, and the relative importance of different assembly processes can vary under different conditions and between different microbial groups.

scholarly journals Hill-based dissimilarity indices and null models for analysis of microbial community assembly

2020 ◽  
Author(s):  
Oskar Modin ◽  
Raquel Liébana ◽  
Soroush Saheb-Alam ◽  
Britt-Marie Wilén ◽  
Carolina Suarez ◽  
...  
Keyword(s):  
Microbial Community ◽  
Microbial Communities ◽  
Community Assembly ◽  
Null Model ◽  
Amplicon Sequencing ◽  
Null Models ◽  
Marker Genes ◽  
Experimental Systems ◽  
Microbial Community Assembly ◽  
The Impact

Abstract Background: High-throughput amplicon sequencing of marker genes, such as the 16S rRNA gene in Bacteria and Archaea, provides a wealth of information about the composition of microbial communities. To quantify differences between samples and draw conclusions about factors affecting community assembly, dissimilarity indices are typically used. However, results are subject to several biases and data interpretation can be challenging. The Jaccard and Bray-Curtis indices, which are often used to quantify taxonomic dissimilarity, are not necessarily the most logical choices. Instead, we argue that Hill-based indices, which make it possible to systematically investigate the impact of relative abundance on dissimilarity, should be used for robust analysis of data. In combination with a null model, mechanisms of microbial community assembly can be analyzed. Here, we also introduce a new software, qdiv, which enables rapid calculations of Hill-based dissimilarity indices in combination with null models.Results: Using amplicon sequencing data from two experimental systems, aerobic granular sludge (AGS) reactors and microbial fuel cells (MFC), we show that the choice of dissimilarity index can have considerable impact on results and conclusions. High dissimilarity between replicates because of random sampling effects make incidence-based indices less suited for identifying differences between groups of samples. Determining a consensus table based on count tables generated with different bioinformatic pipelines reduced the number of low-abundant, potentially spurious amplicon sequence variants (ASVs) in the data sets, which led to lower dissimilarity between replicates. Analysis with a combination of Hill-based indices and a null model allowed us to show that different ecological mechanisms acted on different fractions of the microbial communities in the experimental systems.Conclusions: Hill-based indices provide a rational framework for analysis of dissimilarity between microbial community samples. In combination with a null model, the effects of deterministic and stochastic community assembly factors on taxa of different relative abundances can be systematically investigated. Calculations of Hill-based dissimilarity indices in combination with a null model can be done in qdiv, which is freely available as a Python package (https://github.com/omvatten/qdiv). In qdiv, a consensus table can also be determined from several count tables generated with different bioinformatic pipelines.

scholarly journals Using null models to compare bacterial and microeukaryotic metacommunity assembly under shifting environmental conditions

2019 ◽  
Author(s):  
Máté Vass ◽  
Anna J. Székely ◽  
Eva S. Lindström ◽  
Silke Langenheder
Keyword(s):  
Community Assembly ◽  
Environmental Conditions ◽  
Null Model ◽  
Temporal Variations ◽  
18S Rrna Gene ◽  
Rrna Gene ◽  
Historical Contingency ◽  
Selection Processes ◽  
Rrna Gene Sequencing ◽  
Microbial Groups

AbstractTemporal variations in microbial metacommunity structure and assembly processes in response to shifts in environmental conditions are poorly understood. Hence, we conducted a temporal field study by sampling rock pools in four-day intervals during a 5-week period that included strong changes in environmental conditions due to intensive rain. We characterized bacterial and microeukaryote communities by 16S and 18S rRNA gene sequencing, respectively. Using a suite of null-model approaches to assess dynamics in community assembly, we found that strong changes in environmental conditions induced small but significant temporal changes in assembly processes and triggered different responses in bacterial and microeukaryotic metacommunities, promoting distinct selection processes. Incidence-based approaches showed that the assemblies of both communities were mainly governed by stochastic processes. In contrast, abundance-based methods indicated the dominance of historical contingency and unmeasured factors in case of bacteria and microeukaryotes, respectively, which we distinguished from dispersal-related processes using additional tests. Taken together, our study highlights that community assembly processes are not static, and the relative importance of different assembly processes can vary under different conditions and between different microbial groups.

scholarly journals Hill-based dissimilarity indices and null models for analysis of microbial community assembly

2020 ◽  
Author(s):  
Oskar Modin ◽  
Raquel Liébana ◽  
Soroush Saheb-Alam ◽  
Britt-Marie Wilén ◽  
Carolina Suarez ◽  
...  
Keyword(s):  
Microbial Community ◽  
Microbial Communities ◽  
Community Assembly ◽  
Null Model ◽  
Amplicon Sequencing ◽  
Null Models ◽  
Marker Genes ◽  
Experimental Systems ◽  
Microbial Community Assembly ◽  
The Impact

Abstract Background: High-throughput amplicon sequencing of marker genes, such as the 16S rRNA gene in Bacteria and Archaea, provides a wealth of information about the composition of microbial communities. To quantify differences between samples and draw conclusions about factors affecting community assembly, dissimilarity indices are typically used. However, results are subject to several biases and data interpretation can be challenging. The Jaccard and Bray-Curtis indices, which are often used to quantify taxonomic dissimilarity, are not necessarily the most logical choices. Instead, we argue that Hill-based indices, which make it possible to systematically investigate the impact of relative abundance on dissimilarity, should be used for robust analysis of data. In combination with a null model, mechanisms of microbial community assembly can be analyzed. Here, we also introduce a new software, qdiv, which enables rapid calculations of Hill-based dissimilarity indices in combination with null models.Results: Using amplicon sequencing data from two experimental systems, aerobic granular sludge (AGS) reactors and microbial fuel cells (MFC), we show that the choice of dissimilarity index can have considerable impact on results and conclusions. High dissimilarity between replicates because of random sampling effects make incidence-based indices less suited for identifying differences between groups of samples. Determining a consensus table based on count tables generated with different bioinformatic pipelines reduced the number of low-abundant, potentially spurious amplicon sequence variants (ASVs) in the data sets, which led to lower dissimilarity between replicates. Analysis with a combination of Hill-based indices and a null model allowed us to show that different ecological mechanisms acted on different fractions of the microbial communities in the experimental systems.Conclusions: Hill-based indices provide a rational framework for analysis of dissimilarity between microbial community samples. In combination with a null model, the effects of deterministic and stochastic community assembly factors on taxa of different relative abundances can be systematically investigated. Calculations of Hill-based dissimilarity indices in combination with a null model can be done in qdiv, which is freely available as a Python package (https://github.com/omvatten/qdiv). In qdiv, a consensus table can also be determined from several count tables generated with different bioinformatic pipelines.

scholarly journals Hill-based dissimilarity indices and null models for analysis of microbial community assembly

Microbiome ◽  
2020 ◽  
Vol 8 (1) ◽  
Author(s):  
Oskar Modin ◽  
Raquel Liébana ◽  
Soroush Saheb-Alam ◽  
Britt-Marie Wilén ◽  
Carolina Suarez ◽  
...  
Keyword(s):  
Microbial Community ◽  
Microbial Communities ◽  
Community Assembly ◽  
Null Model ◽  
Amplicon Sequencing ◽  
Null Models ◽  
Marker Genes ◽  
Experimental Systems ◽  
Microbial Community Assembly ◽  
The Impact

Abstract Background High-throughput amplicon sequencing of marker genes, such as the 16S rRNA gene in Bacteria and Archaea, provides a wealth of information about the composition of microbial communities. To quantify differences between samples and draw conclusions about factors affecting community assembly, dissimilarity indices are typically used. However, results are subject to several biases, and data interpretation can be challenging. The Jaccard and Bray-Curtis indices, which are often used to quantify taxonomic dissimilarity, are not necessarily the most logical choices. Instead, we argue that Hill-based indices, which make it possible to systematically investigate the impact of relative abundance on dissimilarity, should be used for robust analysis of data. In combination with a null model, mechanisms of microbial community assembly can be analyzed. Here, we also introduce a new software, qdiv, which enables rapid calculations of Hill-based dissimilarity indices in combination with null models. Results Using amplicon sequencing data from two experimental systems, aerobic granular sludge (AGS) reactors and microbial fuel cells (MFC), we show that the choice of dissimilarity index can have considerable impact on results and conclusions. High dissimilarity between replicates because of random sampling effects make incidence-based indices less suited for identifying differences between groups of samples. Determining a consensus table based on count tables generated with different bioinformatic pipelines reduced the number of low-abundant, potentially spurious amplicon sequence variants (ASVs) in the data sets, which led to lower dissimilarity between replicates. Analysis with a combination of Hill-based indices and a null model allowed us to show that different ecological mechanisms acted on different fractions of the microbial communities in the experimental systems. Conclusions Hill-based indices provide a rational framework for analysis of dissimilarity between microbial community samples. In combination with a null model, the effects of deterministic and stochastic community assembly factors on taxa of different relative abundances can be systematically investigated. Calculations of Hill-based dissimilarity indices in combination with a null model can be done in qdiv, which is freely available as a Python package (https://github.com/omvatten/qdiv). In qdiv, a consensus table can also be determined from several count tables generated with different bioinformatic pipelines.

scholarly journals Trophic States Regulate Assembly Processes and Network Structures of Picophytoplankton Communities in Subtropical Coastal Ecosystems

2020 ◽  
Author(s):  
Xing Chen ◽  
Huaxian Zhao ◽  
Gonglingxia Jiang ◽  
Jinli Tang ◽  
Qiangsheng Xu ◽  
...  
Keyword(s):  
Community Assembly ◽  
Anthropogenic Activities ◽  
Alpha Diversity ◽  
Amplicon Sequencing ◽  
Coastal Ecosystems ◽  
Network Structures ◽  
Coastal Eutrophication ◽  
Nitrogen And Phosphorus ◽  
Ecological Processes ◽  
Deterministic Processes

Abstract Background: Long-term coastal eutrophication especially in semi-enclosed marine areas is driven by increased amounts of nutrients derived from anthropogenic activities. Given that accelerating nutrients may constitute a strong environmental filter, understanding the diversity, assembly process and co-occurrence pattern of picophytoplankton communities in response to increasing coastal eutrophication is clearly of great importance. Results: We investigated picophytoplankton community changes using rbcL gene amplicon sequencing. The results exhibited that the alpha diversity (ANOVA, p < 0.001) and beta diversity (ANOSIM, p < 0.001) were significantly different among eutrophic states. Further, phylogenetic based β-nearest taxon distance analyses revealed that stochastic processes mainly provided 69.26% contribution to picophytoplankton community assembly, whereas deterministic processes dominated community assembly in a heavy eutrophic state. Integrated co-occurrence networks modularly responded to eutrophic states and revealed that keystone taxa mainly belonged to the oligo eutrophic group, which may play fundamental roles in network persistence. Importantly, increased environmental disturbances, such as nitrogen and phosphorus nutrients, could alter picophytoplankton community structure and disrupt ecological processes. Conclusion: Stochastic and deterministic processes simultaneously influenced the assembly of picophytoplankton communities in the subtropical coastal ecosystems. Eutrophic disturbances alert the assembly processes and network structures of picophytoplankton community. Our findings promote the understanding of fundamental ecological processes along eutrophic gradients in subtropical coastal ecosystems.

scholarly journals Contrasting Patterns in Diversity and Community Assembly of Phragmites australis Root-Associated Bacterial Communities from Different Seasons

2020 ◽  
Vol 86 (14) ◽  
Author(s):  
Rujia He ◽  
Jin Zeng ◽  
Dayong Zhao ◽  
Rui Huang ◽  
Zhongbo Yu ◽  
...  
Keyword(s):  
Phragmites Australis ◽  
Community Assembly ◽  
Bacterial Communities ◽  
Aquatic Ecosystems ◽  
Null Model ◽  
Relative Importance ◽  
Bulk Sediment ◽  
Β Diversity ◽  
Different Seasons ◽  
Deterministic Processes

ABSTRACT The common reed (Phragmites australis), a cosmopolitan aquatic macrophyte, plays an important role in the structure and function of aquatic ecosystems. We compared bacterial community compositions (BCCs) and their assembly processes in the root-associated compartments (i.e., rhizosphere and endosphere) of reed and bulk sediment between summer and winter. The BCCs were analyzed using high-throughput sequencing of the bacterial 16S rRNA gene; meanwhile, null-model analysis was employed to characterize their assembly mechanisms. The sources of the endosphere BCCs were quantitatively examined using SourceTracker from bulk sediment, rhizosphere, and seed. We observed the highest α-diversity and the lowest β-diversity of BCCs in the rhizosphere in both seasons. We also found a significant increase in α- and β-diversity in summer compared to that in winter among the three compartments. It was demonstrated that rhizosphere sediments were the main source (∼70%) of root endosphere bacteria during both seasons. Null-model tests indicated that stochastic processes primarily affected endosphere BCCs, whereas both deterministic and stochastic processes dictated bacterial assemblages of the rhizosphere, with the relative importance of stochastic versus deterministic processes depending on the season. This study suggests that multiple mechanisms of bacterial selection and community assembly exist both inside and outside P. australis roots in different seasons. IMPORTANCE Understanding the composition and assembly mechanisms of root-associated microbial communities of plants is crucial for understanding the interactions between plants and soil. Most previous studies of the plant root-associated microbiome focused on model and economic plants, with fewer temporal or seasonal investigations. The assembly mechanisms of root-associated bacterial communities in different seasons remain poorly known, especially for the aquatic macrophytes. In this study, we compared the diversity, composition, and relative importance of two different assembly processes (stochastic and deterministic processes) of bacterial communities associated with bulk sediment and the rhizosphere and endosphere of Phragmites australis in summer and winter. While we found apparent differences in composition, diversity, and assembly processes of bacterial communities among different compartments, season played important roles in determining BCCs and their diversity patterns and assemblages. We also found that endosphere bacteria mainly originated from the rhizosphere. The results add new knowledge regarding the plant-microbe interactions in aquatic ecosystems.

scholarly journals The Composition and Assembly of Bacterial Communities across the Rhizosphere and Phyllosphere Compartments of Phragmites Australis

Diversity ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 98 ◽  
Author(s):  
Qi Zhou ◽  
Xiaomin Zhang ◽  
Rujia He ◽  
Shuren Wang ◽  
Congcong Jiao ◽  
...  
Keyword(s):  
Bacterial Community ◽  
Phragmites Australis ◽  
Bacterial Communities ◽  
High Throughput Sequencing ◽  
Null Model ◽  
Rrna Gene ◽  
Rare Taxa ◽  
Alpha And Beta Diversity ◽  
Deterministic Processes ◽  
The Difference

The rhizosphere and the phyllosphere represent two different epiphytic compartments of host plant, which are closely related to plant growth, health, and productivity. However, the understanding of the diversity, composition, and assembly of the bacterial communities in different epiphytic microenvironments of large emerged macrophytes has remained elusive, especially the abundant and rare taxa across rhizosphere and phyllosphere communities. In this study, we collected samples of two different epiphytic compartments (rhizosphere and phyllosphere) of Phragmites australis. Both 16S rRNA gene-based high-throughput sequencing and null-model analysis were employed to determine the difference in the composition and assembly of above-mentioned epiphytic bacterial communities. Our results indicated that bacterial communities of rhizosphere exhibited higher diversity and richness than those of phyllosphere. Deterministic processes dominated the assembly of bacterial community in both compartments, and stochastic processes contributed a certain proportion (30.30%) in the assembly of phyllosphere bacterial community. We also found that rare taxa contributed more significantly to the alpha- and beta-diversity of bacterial community than those of abundant taxa. The obtained data are useful for better understanding the bacterial community of different epiphytic compartments of P. australis.

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