scholarly journals Circular Economy of Anaerobic Biofilm Microbiomes: A Meta-Analysis Framework for Re-exploration of Amplicon Sequencing Data

2020 ◽  
Author(s):  
Ciara Keating ◽  
Anna Christine Trego ◽  
William Sloan ◽  
Vincent O’Flaherty ◽  
Umer Zeeshan Ijaz
Keyword(s):  
Data Mining ◽  
Wastewater Treatment ◽  
Anaerobic Digestion ◽  
Microbial Communities ◽  
High Throughput Sequencing ◽  
Meta Analysis ◽  
Illumina Miseq ◽  
Amplicon Sequencing ◽  
Sequencing Data ◽  
Analysis Workflow

AbstractUse of high-throughput sequencing is widespread in efforts to understand the microbial communities in natural and engineered systems. Many built ecosystems, in particular those used for engineered wastewater treatment, have harnessed the metabolic capacity of complex microbial communities for the effective removal and recovery of organic pollutants. Recent efforts to better understand and precisely engineer such systems have increasingly used high-throughput sequencing to map the structure and function of wastewater treatment microbiomes. An enormous amount of data is readily available on online repositories such as the National Center for Biotechnology Information Short Read Archive (NCBI SRA). Here, we describe and provide an optimised meta-analysis workflow to utilise this resource to collate heterogenous studies together for anaerobic digestion research. We analysed 16S rRNA gene Illumina Miseq amplicon sequencing data from 31 anaerobic digestion studies (from high-rate digesters), including >1,300 samples. Additionally, we compare several methodological choices: extraction method, v-region, taxonomical database, and the classifier. We demonstrate that collation of data from multiple v-regions can be achieved by using only the taxa for which sequences are available in the reference databases, without losses in diversity trends. This is made possible by focusing on alternative strategies for taxonomic assignments, namely, bayesian lowest common ancestor (BLCA) algorithm which offers increased resolution to the traditional naïve bayesian classifier (NBC). While we demonstrate this using an anaerobic digestion wastewater treatment dataset, this methodology can be translated to perform meta-analysis on amplicon sequences in any field. These findings not only provide a roadmap for meta-analysis in any field, but additionally provide an opportunity to reuse extensive data resources to ultimately advance knowledge of wastewater treatment systems.ImportanceIn this study, we have combined sequencing data from 31 individual studies with the purpose of identifying a meta-analysis workflow which can accurately collate data derived from sequencing different v-regions with minimal data loss and more accurate diversity patterns. While we have used Anaerobic Digestion (AD) communities for our proof-of-concept, our workflow (Fig 1) can be translated to any Illumina MiSeq meta-analysis study, in any field. Thereby, we provide the foundation for intensive data mining of existing amplicon sequencing resources. Such data-mining can provide a global perspective on complex microbial communities.Graphical Abstract

scholarly journals A conceptual framework modeling of functional microbial communities in wastewater treatment electro-bioreactors

2020 ◽  
Vol 82 (12) ◽  
pp. 3047-3061
Author(s):  
Nancy A. ElNaker ◽  
Abdelsattar M. Sallam ◽  
El-Sayed M. El-Sayed ◽  
H. El Ghandoor ◽  
M. S. Talaat ◽  
...  
Keyword(s):  
Wastewater Treatment ◽  
Conceptual Framework ◽  
Microbial Communities ◽  
Conceptual Model ◽  
High Throughput Sequencing ◽  
Microbial Community Composition ◽  
Operating Conditions ◽  
Rrna Gene ◽  
Sequencing Data ◽  
Operational Parameters

Abstract Understanding the microbial ecology of a system allows linking members of the community and their metabolic functions to the performance of the wastewater bioreactor. This study provided a comprehensive conceptual framework for microbial communities in wastewater treatment electro-bioreactors (EBRs). The model was based on data acquired from monitoring the effect of altering different bioreactor operational parameters, such as current density and hydraulic retention time, on the microbial communities of an EBR and its nutrient removal efficiency. The model was also based on the 16S rRNA gene high-throughput sequencing data analysis and bioreactor efficiency data. The collective data clearly demonstrated that applying various electric currents affected the microbial community composition and stability and the reactor efficiency in terms of chemical oxygen demand, N and P removals. Moreover, a schematic that recommends operating conditions that are tailored to the type of wastewater that needs to be treated based on the functional microbial communities enriched at specific operating conditions was suggested. In this study, a conceptual model as a simplified representation of the behavior of microbial communities in EBRs was developed. The proposed conceptual model can be used to predict how biological treatment of wastewater in EBRs can be improved by varying several operating conditions.

scholarly journals Pollutant-Removing Biofilter Strains Associated with High Ammonia and Hydrogen Sulfide Removal Rate in a Livestock Wastewater Treatment Facility

2021 ◽  
Vol 13 (13) ◽  
pp. 7358
Author(s):  
Dong-Hyun Kim ◽  
Hyun-Sik Yun ◽  
Young-Saeng Kim ◽  
Jong-Guk Kim
Keyword(s):  
Wastewater Treatment ◽  
Hydrogen Sulfide ◽  
Microbial Community ◽  
Microbial Communities ◽  
Illumina Miseq ◽  
Illumina Miseq Sequencing ◽  
Miseq Sequencing ◽  
Treatment Facility ◽  
Livestock Wastewater ◽  
Wastewater Treatment Facility

This study analyzed the microbial community metagenomically to determine the cause of the functionality of a livestock wastewater treatment facility that can effectively remove pollutants, such as ammonia and hydrogen sulfide. Illumina MiSeq sequencing was used in analyzing the composition and structure of the microbial community, and the 16S rRNA gene was used. Through Illumina MiSeq sequencing, information such as diversity indicators as well as the composition and structure of microbial communities present in the livestock wastewater treatment facility were obtained, and differences between microbial communities present in the investigated samples were compared. The number of reads, operational taxonomic units, and species richness were lower in influent sample (NLF), where the wastewater enters, than in effluent sample (NL), in which treated wastewater is found. This difference was greater in June 2019 than in January 2020, and the removal rates of ammonia (86.93%) and hydrogen sulfide (99.72%) were also higher in June 2019. In both areas, the community composition was similar in January 2020, whereas the influent sample (NLF) and effluent sample (NL) areas in June 2019 were dominated by Proteobacteria (76.23%) and Firmicutes (67.13%), respectively. Oleiphilaceae (40.89%) and Thioalkalibacteraceae (12.91%), which are related to ammonia and hydrogen sulfide removal, respectively, were identified in influent sample (NLF) in June 2019. They were more abundant in June 2019 than in January 2020. Therefore, the functionality of the livestock wastewater treatment facility was affected by characteristics, including the composition of the microbial community. Compared to Illumina MiSeq sequencing, fewer species were isolated and identified in both areas using culture-based methods, suggesting Illumina MiSeq sequencing as a powerful tool to determine the relevance of microbial communities for pollutant removal.

scholarly journals Extremely Halophilic Biohydrogen Producing Microbial Communities from High-Salinity Soil and Salt Evaporation Pond

Fuels ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 241-252
Author(s):  
Dyah Asri Handayani Taroepratjeka ◽  
Tsuyoshi Imai ◽  
Prapaipid Chairattanamanokorn ◽  
Alissara Reungsang
Keyword(s):  
Microbial Communities ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
High Salinity ◽  
Amplicon Sequencing ◽  
Spatial Proximity ◽  
Lignocellulosic Waste ◽  
Evaporation Pond ◽  
Operational Taxonomic Units ◽  
Determining Factor

Extreme halophiles offer the advantage to save on the costs of sterilization and water for biohydrogen production from lignocellulosic waste after the pretreatment process with their ability to withstand extreme salt concentrations. This study identifies the dominant hydrogen-producing genera and species among the acclimatized, extremely halotolerant microbial communities taken from two salt-damaged soil locations in Khon Kaen and one location from the salt evaporation pond in Samut Sakhon, Thailand. The microbial communities’ V3–V4 regions of 16srRNA were analyzed using high-throughput amplicon sequencing. A total of 345 operational taxonomic units were obtained and the high-throughput sequencing confirmed that Firmicutes was the dominant phyla of the three communities. Halanaerobium fermentans and Halanaerobacter lacunarum were the dominant hydrogen-producing species of the communities. Spatial proximity was not found to be a determining factor for similarities between these extremely halophilic microbial communities. Through the study of the microbial communities, strategies can be developed to increase biohydrogen molar yield.

scholarly journals A meta-analysis reveals the environmental and host factors shaping the structure and function of the shrimp microbiota

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e5382 ◽  
Author(s):  
Fernanda Cornejo-Granados ◽  
Luigui Gallardo-Becerra ◽  
Miriam Leonardo-Reza ◽  
Juan Pablo Ochoa-Romo ◽  
Adrian Ochoa-Leyva
Keyword(s):  
Developmental Stage ◽  
High Throughput Sequencing ◽  
Meta Analysis ◽  
Biological Factor ◽  
Rrna Gene ◽  
Wild Type ◽  
Biological Factors ◽  
Sequencing Data ◽  
Freshwater Environment ◽  
The Impact

The shrimp or prawn is the most valuable traded marine product in the world market today and its microbiota plays an essential role in its development, physiology, and health. The technological advances and dropping costs of high-throughput sequencing have increased the number of studies characterizing the shrimp microbiota. However, the application of different experimental and bioinformatics protocols makes it difficult to compare different studies to reach general conclusions about shrimp microbiota. To meet this necessity, we report the first meta-analysis of the microbiota from freshwater and marine shrimps using all publically available sequences of the 16S ribosomal gene (16S rRNA gene). We obtained data for 199 samples, in which 63.3% were from marine (Alvinocaris longirostris, Litopenaeus vannamei and Penaeus monodon), and 36.7% were from freshwater (Macrobrachium asperulum, Macrobrachium nipponense, Macrobranchium rosenbergii, Neocaridina denticulata) shrimps. Technical variations among studies, such as selected primers, hypervariable region, and sequencing platform showed a significant impact on the microbiota structure. Additionally, the ANOSIM and PERMANOVA analyses revealed that the most important biological factor in structuring the shrimp microbiota was the marine and freshwater environment (ANOSIM R = 0.54, P = 0.001; PERMANOVA pseudo-F = 21.8, P = 0.001), where freshwater showed higher bacterial diversity than marine shrimps. Then, for marine shrimps, the most relevant biological factors impacting the microbiota composition were lifestyle (ANOSIM R = 0.341, P = 0.001; PERMANOVA pseudo-F = 8.50, P = 0.0001), organ (ANOSIM R = 0.279, P = 0.001; PERMANOVA pseudo-F = 6.68, P = 0.001) and developmental stage (ANOSIM R = 0.240, P = 0.001; PERMANOVA pseudo-F = 5.05, P = 0.001). According to the lifestyle, organ, developmental stage, diet, and health status, the highest diversity were for wild-type, intestine, adult, wild-type diet, and healthy samples, respectively. Additionally, we used PICRUSt to predict the potential functions of the microbiota, and we found that the organ had more differentially enriched functions (93), followed by developmental stage (12) and lifestyle (9). Our analysis demonstrated that despite the impact of technical and bioinformatics factors, the biological factors were also statistically significant in shaping the microbiota. These results show that cross-study comparisons are a valuable resource for the improvement of the shrimp microbiota and microbiome fields. Thus, it is important that future studies make public their sequencing data, allowing other researchers to reach more powerful conclusions about the microbiota in this non-model organism. To our knowledge, this is the first meta-analysis that aims to define the shrimp microbiota.

scholarly journals Natrix: a Snakemake-based workflow for processing, clustering, and taxonomically assigning amplicon sequencing reads

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Marius Welzel ◽  
Anja Lange ◽  
Dominik Heider ◽  
Michael Schwarz ◽  
Bernd Freisleben ◽  
...  
Keyword(s):  
High Throughput Sequencing ◽  
Workflow Management ◽  
Amplicon Sequencing ◽  
Version Control ◽  
Marker Genes ◽  
Sequencing Data ◽  
Taxonomic Assignment ◽  
Ecological Processes ◽  
Link Type ◽  
User Friendly

Abstract Background Sequencing of marker genes amplified from environmental samples, known as amplicon sequencing, allows us to resolve some of the hidden diversity and elucidate evolutionary relationships and ecological processes among complex microbial communities. The analysis of large numbers of samples at high sequencing depths generated by high throughput sequencing technologies requires efficient, flexible, and reproducible bioinformatics pipelines. Only a few existing workflows can be run in a user-friendly, scalable, and reproducible manner on different computing devices using an efficient workflow management system. Results We present Natrix, an open-source bioinformatics workflow for preprocessing raw amplicon sequencing data. The workflow contains all analysis steps from quality assessment, read assembly, dereplication, chimera detection, split-sample merging, sequence representative assignment (OTUs or ASVs) to the taxonomic assignment of sequence representatives. The workflow is written using Snakemake, a workflow management engine for developing data analysis workflows. In addition, Conda is used for version control. Thus, Snakemake ensures reproducibility and Conda offers version control of the utilized programs. The encapsulation of rules and their dependencies support hassle-free sharing of rules between workflows and easy adaptation and extension of existing workflows. Natrix is freely available on GitHub (https://github.com/MW55/Natrix) or as a Docker container on DockerHub (https://hub.docker.com/r/mw55/natrix). Conclusion Natrix is a user-friendly and highly extensible workflow for processing Illumina amplicon data.

scholarly journals Meta-Analysis of Microbial Communities in Hot Springs: Recurrent Taxa and Complex Shaping Factors beyond pH and Temperature

2020 ◽  
Vol 8 (6) ◽  
pp. 906 ◽  
Author(s):  
Francisco L. Massello ◽  
Chia Sing Chan ◽  
Kok-Gan Chan ◽  
Kian Mau Goh ◽  
Edgardo Donati ◽  
...  
Keyword(s):  
Microbial Communities ◽  
Metabolic Profile ◽  
Hot Springs ◽  
Meta Analysis ◽  
Extreme Environments ◽  
Alpha Diversity ◽  
Amplicon Sequencing ◽  
Phylogenetic Distance ◽  
Microbial Profile ◽  
The World

The study of microbial communities from extreme environments is a fascinating topic. With every study, biologists and ecologists reveal interesting facts and questions that dispel the old belief that these are inhospitable environments. In this work, we assess the microbial diversity of three hot springs from Neuquén, Argentina, using high-throughput amplicon sequencing. We predicted a distinct metabolic profile in the acidic and the circumneutral samples, with the first ones being dominated by chemolithotrophs and the second ones by chemoheterotrophs. Then, we collected data of the microbial communities of hot springs around the world in an effort to comprehend the roles of pH and temperature as shaping factors. Interestingly, there was a covariation between both parameters and the phylogenetic distance between communities; however, neither of them could explain much of the microbial profile in an ordination model. Moreover, there was no correlation between alpha diversity and these parameters. Therefore, the microbial communities’ profile seemed to have complex shaping factors beyond pH and temperature. Lastly, we looked for taxa associated with different environmental conditions. Several such taxa were found. For example, Hydrogenobaculum was frequently present in acidic springs, as was the Sulfolobaceae family; on the other hand, Candidatus Hydrothermae phylum was strongly associated with circumneutral conditions. Interestingly, some singularities related to sites featuring certain taxa were also observed.

scholarly journals Synthetic Sequencing Standards: A Guide to Database Choice for Rumen Microbiota Amplicon Sequencing Analysis

2020 ◽  
Vol 11 ◽  
Author(s):  
Paul E. Smith ◽  
Sinead M. Waters ◽  
Ruth Gómez Expósito ◽  
Hauke Smidt ◽  
Ciara A. Carberry ◽  
...  
Keyword(s):  
High Throughput Sequencing ◽  
Cost Effective ◽  
Amplicon Sequencing ◽  
Gas Production ◽  
Reference Database ◽  
Specific Reference ◽  
Sequencing Analysis ◽  
Sequencing Data ◽  
Rumen Microbiota ◽  
Reference Databases

Our understanding of complex microbial communities, such as those residing in the rumen, has drastically advanced through the use of high throughput sequencing (HTS) technologies. Indeed, with the use of barcoded amplicon sequencing, it is now cost effective and computationally feasible to identify individual rumen microbial genera associated with ruminant livestock nutrition, genetics, performance and greenhouse gas production. However, across all disciplines of microbial ecology, there is currently little reporting of the use of internal controls for validating HTS results. Furthermore, there is little consensus of the most appropriate reference database for analyzing rumen microbiota amplicon sequencing data. Therefore, in this study, a synthetic rumen-specific sequencing standard was used to assess the effects of database choice on results obtained from rumen microbial amplicon sequencing. Four DADA2 reference training sets (RDP, SILVA, GTDB, and RefSeq + RDP) were compared to assess their ability to correctly classify sequences included in the rumen-specific sequencing standard. In addition, two thresholds of phylogenetic bootstrapping, 50 and 80, were applied to investigate the effect of increasing stringency. Sequence classification differences were apparent amongst the databases. For example the classification of Clostridium differed between all databases, thus highlighting the need for a consistent approach to nomenclature amongst different reference databases. It is hoped the effect of database on taxonomic classification observed in this study, will encourage research groups across various microbial disciplines to develop and routinely use their own microbiome-specific reference standard to validate analysis pipelines and database choice.

scholarly journals System Biology Modeling with Compositional Microbiome Data Reveals Personalized Gut Microbial Dynamics and Keystone Species

2018 ◽  
Author(s):  
Chenhao Li ◽  
Lisa Tucker-Kellogg ◽  
Niranjan Nagarajan
Keyword(s):  
Microbial Communities ◽  
High Throughput Sequencing ◽  
Community Dynamics ◽  
Keystone Species ◽  
Microbial Interactions ◽  
Natural Environments ◽  
Sequencing Data ◽  
Predator Prey ◽  
Public Datasets ◽  
Microbiome Data

AbstractA growing body of literature points to the important roles that different microbial communities play in diverse natural environments and the human body. The dynamics of these communities is driven by a range of microbial interactions from symbiosis to predator-prey relationships, the majority of which are poorly understood, making it hard to predict the response of the community to different perturbations. With the increasing availability of high-throughput sequencing based community composition data, it is now conceivable to directly learn models that explicitly define microbial interactions and explain community dynamics. The applicability of these approaches is however affected by several experimental limitations, particularly the compositional nature of sequencing data. We present a new computational approach (BEEM) that addresses this key limitation in the inference of generalised Lotka-Volterra models (gLVMs) by coupling biomass estimation and model inference in an expectation maximization like algorithm (BEEM). Surprisingly, BEEM outperforms state-of-the-art methods for inferring gLVMs, while simultaneously eliminating the need for additional experimental biomass data as input. BEEM’s application to previously inaccessible public datasets (due to the lack of biomass data) allowed us for the first time to analyse microbial communities in the human gut on a per individual basis, revealing personalised dynamics and keystone species.

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