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Validation of 16S rRNA Gene Sequencing and Metagenomics for Evaluating Microbial Immigration in a Methanogenic Bioreactor
Abstract
To quantitatively evaluate the impact of microbial immigration from an upstream community on the microbial assembly of a downstream community, an ecological genomics (ecogenomics)-based mass balance (EGMB) model coupled with 16S rRNA gene sequencing was previously developed. In this study, a mock community was used to further validate the EGMB models and demonstrate the feasibility of using metagenome-based EGMB model to reveal both microbial activity and function. The mock community consisting of Aeromonas, Escherichia, and Pseudomonas was fed into a lab-scale methanogenic bioreactor together with dissolved organic substrate. Using qPCR, 16S rRNA gene, 16S rRNA gene copy number normalization (GCN), and metagenome, results showed highly comparable community profiles in the feed. In the bioreactor, Aeromonas and Pseudomonas exhibited negative growth rates throughout the experiment by all approaches. Escherichia's growth rate was negative by most biomarkers but was slightly positive by 16S rRNA gene. Still, all approaches showed a decreasing trend toward negative in the growth rate of Escherichia as reactor operation time increased. Uncultivated populations of phyla Desulfobacterota, Chloroflexi, Actinobacteriota, and Spirochaetota were observed to increase in abundance, suggesting their contribution in degrading the feed biomass. Based on metabolic reconstruction of metagenomes, these populations possessed functions of hydrolysis, fermentation, fatty acid degradation, or acetate oxidation. Overall results supported the application of both 16S rRNA gene- and metagenome-based EGMB models to measure the growth rate of microbes in the bioreactor, and the latter had advantage in providing insights into the microbial functions of uncultivated populations.
Ultrasound and combined alkaline–ultrasound pretreatment (AUP) strategies were examined for primary sewage sludge (SS) disintegration and were utilized to evaluate the degree of solubilization (DS). Further, the pretreated primary SS was operated in microbial electrolysis cells (MECs) to maximize methane production and thereby improve the reactor performance. The highest DS of 67.2% of primary SS was recorded with the AUP. MEC reactors operated with the AUP showed the highest methane production (240 ± 6.4 mL g VSin−1). VS (61.1%) and COD (72.2%) removal in the MEC ALK-US showed the best organic matter removal efficiency. In the modified Gompertz analysis, the substrate with the highest degree of solubilization (AUP) had the shortest lag phase (0.2 ± 0.1 d). This implies that forced hydrolysis via pretreatment could enhance biodegradability, thereby making it easy for microorganisms to consume and leading to improved MEC performances. Microbial analysis implicitly demonstrated that pretreatment expedited the growth of hydrolytic bacteria (Bacteroidetes and Firmicutes), and a syntrophic interaction with electroactive microorganisms (Smithella) and hydrogenotrophic methanogens (Methanoculleus) was enriched in the MECs with AUP sludge. This suggests that the AUP strategy could be useful to enhance anaerobic digestion performance and provide a new perspective on treating primary SS in an economical way.
This study evaluated the effects of sodium on anaerobic biomass from the second-stage reactor of a two-stage anaerobic digester. The results indicated that methanogens showed a relatively high sodium tolerance of 2.4 g Na+ L−1. Microbial community analysis showed that viable Methanomicrobiales was the most abundant population by a combined propidium monoazide cross-linking quantitative polymerase chain reaction technique. There was a population shift towards higher abundance of Thermotoga (0.02%), Clostridium (2.50%) and Methanoculleus (13.80%). Biomass activity in relation to increased sodium concentrations was investigated with the adenosine triphosphate test coupled with extracellular polymeric substances measurement. The results showed biomass activity decreased from 33 to 16 µg g−1 volatile suspended solids as sodium concentrations increased from 1.3 to 9.1 g Na+ L−1. Higher EPS production, particularly a greater predominance of carbohydrates, was stimulated by higher sodium concentrations. This study provides insights into the superiority of sodium tolerance of two-stage anaerobic digester in compared with a single-stage anaerobic system.
Even though automated functional annotation of genes represents a fundamental step in most genomic and metagenomic workflows, it remains challenging at large scales. Here, we describe a major upgrade to eggNOG-mapper, a tool for functional annotation based on precomputed orthology assignments, now optimized for vast (meta)genomic data sets. Improvements in version 2 include a full update of both the genomes and functional databases to those from eggNOG v5, as well as several efficiency enhancements and new features. Most notably, eggNOG-mapper v2 now allows for: (i) de novo gene prediction from raw contigs, (ii) built-in pairwise orthology prediction, (iii) fast protein domain discovery, and (iv) automated GFF decoration. eggNOG-mapper v2 is available as a standalone tool or as an online service at http://eggnog-mapper.embl.de.
Interspecies hydrogen transfer (IHT) and direct interspecies electron transfer (DIET) are two syntrophy models for methanogenesis. Their relative importance in methanogenic environments is still unclear. Our recent discovery of a novel species Candidatus Geobacter eutrophica with the genetic potential of IHT and DIET may serve as a model species to address this knowledge gap. To experimentally demonstrate its DIET ability, we performed electrochemical enrichment of Ca. G. eutrophica-dominating communities under 0 and 0.4 V vs. Ag/AgCl based on the presumption that DIET and extracellular electron transfer (EET) share similar metabolic pathways. After three batches of enrichment, Geobacter OTU650, which was phylogenetically close to Ca. G. eutrophica, was outcompeted in the control but remained abundant and active under electrochemical stimulation, indicating Ca. G. eutrophica’s EET ability. The high-quality draft genome further showed high phylogenomic similarity with Ca. G. eutrophica, and the genes encoding outer membrane cytochromes and enzymes for hydrogen metabolism were actively expressed. A Bayesian network was trained with the genes encoding enzymes for alcohol metabolism, hydrogen metabolism, EET, and methanogenesis from dominant fermentative bacteria, Geobacter, and Methanobacterium. Methane production could not be accurately predicted when the genes for IHT were in silico knocked out, inferring its more important role in methanogenesis. The genomics-enabled machine learning modeling approach can provide predictive insights into the importance of IHT and DIET.
In this paper we compared taxonomic results obtained by metataxonomics (16S rRNA gene sequencing) and metagenomics (whole shotgun metagenomic sequencing) to investigate their reliability for bacteria profiling, studying the chicken gut as a model system. The experimental conditions included two compartments of gastrointestinal tracts and two sampling times. We compared the relative abundance distributions obtained with the two sequencing strategies and then tested their capability to distinguish the experimental conditions. The results showed that 16S rRNA gene sequencing detects only part of the gut microbiota community revealed by shotgun sequencing. Specifically, when a sufficient number of reads is available, Shotgun sequencing has more power to identify less abundant taxa than 16S sequencing. Finally, we showed that the less abundant genera detected only by shotgun sequencing are biologically meaningful, being able to discriminate between the experimental conditions as much as the more abundant genera detected by both sequencing strategies.
The genus Escherichia comprises five species and at least five lineages currently not assigned to any species, termed ‘ Escherichia cryptic clades’. We isolated an Escherichia strain from an international traveller and resolved the complete DNA sequence of the chromosome and an IncI multidrug resistance plasmid using Illumina and Nanopore whole-genome sequencing (WGS). Strain OPT1704 T can be differentiated from existing Escherichia species using biochemical (VITEK2) and genomic tests [average nucleotide identity (ANI) and digital DNA–DNA hybridization (dDDH)]. Phylogenetic analysis based on alignment of 16S rRNA sequences and 682 concatenated core genes showed similar results. Our analysis further revealed that strain OPT1704 T falls within Escherichia cryptic clade IV and is closely related to cryptic clade III. Combining our analyses with publicly available WGS data of cryptic clades III and IV from Enterobase confirmed the close relationship between clades III and IV (>96 % interclade ANI), warranting assignment of both clades to the same novel species. We propose Escherichia ruysiae sp. nov. as a novel species, encompassing Escherichia cryptic clades III and IV (type strain OPT1704 T =NCCB 100732 T =NCTC 14359 T ).
SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3 194 778 small subunit and 288 717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches.
Fermentation of waste activated sludge (WAS) is an alternative approach to reduce solid wastes while providing valuable soluble products, such as volatile fatty acids and alcohols. This study systematically identified optimal fermentation conditions and key microbial populations by conducting two sets of experiments under different combinations of biochemical and physical parameters. Based on fermentation product concentrations, methane production, and solid removal, fermentation performance was enhanced under the combined treatments of inoculum heat shock (>60°C), pH 5, 55°C, and short solid retention time (<10 days). An ecogenomics-based mass balance (EGMB) approach was used to determine the net growth rates of individual microbial populations, and classified them into four microbial groups: known syntrophs, known methanogens, fermenters, and WAS-associated populations. Their growth rates were observed to be affected by the treatment conditions. The growth rates of syntrophs and fermenters, such as Syntrophomonas and Parabacteroides increased with a decrease in SRT. In contrast, treatment conditions, such as inoculum heat shock and high incubation temperature inhibited the growth of WAS-associated populations, such as Terrimonas and Bryobacter. There were also populations insensitive to the treatment conditions, such as those related to Microbacter and Rikenellaceae. Overall, the EGMB approach clearly revealed the ecological roles of important microbial guilds in the WAS fermentation system, and guided the selection of optimal conditions for WAS fermentation in future pilot-scale operation.
KEGG (https://www.kegg.jp/) is a manually curated resource integrating eighteen databases categorized into systems, genomic, chemical and health information. It also provides KEGG mapping tools, which enable understanding of cellular and organism-level functions from genome sequences and other molecular datasets. KEGG mapping is a predictive method of reconstructing molecular network systems from molecular building blocks based on the concept of functional orthologs. Since the introduction of the KEGG NETWORK database, various diseases have been associated with network variants, which are perturbed molecular networks caused by human gene variants, viruses, other pathogens and environmental factors. The network variation maps are created as aligned sets of related networks showing, for example, how different viruses inhibit or activate specific cellular signaling pathways. The KEGG pathway maps are now integrated with network variation maps in the NETWORK database, as well as with conserved functional units of KEGG modules and reaction modules in the MODULE database. The KO database for functional orthologs continues to be improved and virus KOs are being expanded for better understanding of virus-cell interactions and for enabling prediction of viral perturbations.
Sequencing 16S rRNA gene amplicons is the gold standard to uncover the composition of prokaryotic communities. The presence of multiple copies of this gene makes the community abundance data distorted and gene copy normalization (GCN) necessary for correction. Even though GCN of 16S data provided a picture closer to the metagenome before, it should also be compared with communities of known composition due to the fact that library preparation is prone to methodological biases. Here, we process 16S rRNA gene amplicon data from eleven simple mock communities with DADA2 and estimate the impact of GCN. In all cases, the mock community composition derived from the 16S sequencing differs from those expected, and GCN fails to improve the classification for most of the analysed communities. Our approach provides empirical evidence that GCN does not improve the 16S target sequencing analyses in real scenarios. We therefore question the use of GCN for metataxonomic surveys until a more comprehensive catalogue of copy numbers becomes available.
There is a lack of understanding of the interaction between anammox bacteria and the flanking microbial communities in both freshwater (non-saline) and marine (saline) ecosystems. Here, we present a comparative genome-based exploration of two different anammox bioreactors, through the analysis of 23 metagenome-assembled genomes (MAGs), 12 from freshwater anammox reactor (FWR), and 11 from marine anammox reactor (MWR). To understand the contribution of individual members to community functions, we applied the index of replication (iRep) to determine bacteria that are actively replicating. Using genomic content and iRep information, we provided a potential ecological role for the dominant members of the community based on the reactor operating conditions. In the non-saline system, anammox (Candidatus Brocadia sinica) and auxotrophic neighboring bacteria belonging to the phyla Ignavibacteriae and Chloroflexi might interact to reduce nitrate to nitrite for direct use by anammox bacteria. Whereas, in the saline reactor, anammox bacterium (Ca. Scalindua erythraensis) and flanking community belonging to phyla Planctomycetes (different than anammox bacteria)—which persistently growing in the system—may catabolize detritus and extracellular material and recycle nitrate to nitrite for direct use by anammox bacteria. Despite different microbial communities, there was functional redundancy in both ecosystems. These results signify the potential application of marine anammox bacteria for treating saline N-rich wastewaters.
There are two main strategies known how microorganisms regulate substrate utilization: specialization on one preferred substrate at high concentrations in batch cultures or simultaneous utilization of many substrates at low concentrations in chemostats. However, it remains unclear how microorganisms utilize substrates at low concentrations in the subsurface: do they focus on a single substrate and exhibit catabolite repression or do they de-repress regulation of all catabolic pathways? Here, we investigated the readiness of Geobacter metallireducens to degrade organic substrates under sessile growth in sediment columns in the presence of a mixed community as a model for aquifers. Three parallel columns were filled with sand and flushed with anoxic medium at a constant inflow (18 ml h −1) of the substrate benzoate (1 mM) with non-limiting nitrate concentrations (30 mM) as electron acceptor. Columns were inoculated with the anaerobic benzoate degrader G. metallireducens. Microbial degradation produced concentration gradients of benzoate toward the column outlet. Metagenomics and label-free metaproteomics were used to detect and quantify the protein expression of G. metallireducens. Bulk benzoate concentrations below 0.2 mM led to increased abundance of catabolic proteins involved in utilization of fermentation products and aromatic compounds including the complete upregulation of the toluene-degrading pathway although toluene was not added to the medium. We propose that under sessile conditions and low substrate concentrations G. metallireducens expresses a specific set of catabolic pathways for preferred substrates, even when these substrates are not present.
SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3 194 778 small subunit and 288 717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches.
The GTDB Toolkit (GTDB-Tk) provides objective taxonomic assignments for bacterial and archaeal genomes based on the Genome Taxonomy Database (GTDB). GTDB-Tk is computationally efficient and able to classify thousands of draft genomes in parallel. Here we demonstrate the accuracy of the GTDB-Tk taxonomic assignments by evaluating its performance on a phylogenetically diverse set of 10,156 bacterial and archaeal metagenome-assembled genomes.
Availability:
GTDB-Tk is implemented in Python and licensed under the GNU General Public License v3.0. Source code and documentation are available at: https://github.com/ecogenomics/gtdbtk.
Supplementary information:
Supplementary data are available at Bioinformatics online.
Immigration is a process that can influence the assembly of microbial communities in natural and engineered environments. However, it remains challenging to quantitatively evaluate the contribution of this process to the microbial diversity and function in the receiving ecosystems. Currently used methods, i.e., counting shared microbial species, microbial source tracking, and neutral community model, rely on abundance profile to reveal the extent of overlapping between the upstream and downstream communities. Thus, they cannot suggest the quantitative contribution of immigrants to the downstream community function because activities of individual immigrants are not considered after entering the receiving environment. This limitation can be overcome by using an approach that couples a mass balance model with high-throughput DNA sequencing, i.e., ecogenomics-based mass balance. It calculates the net growth rate of individual microbial immigrants and partitions the entire community into active populations that contribute to the community function and inactive ones that carry minimal function. Linking activities of immigrants to their abundance further provides quantification of the contribution from an upstream environment to the downstream community. Considering only active populations can improve the accuracy of identifying key environmental parameters dictating process performance using methods such as machine learning.
MetaCyc (MetaCyc.org) is a comprehensive reference database of metabolic pathways and enzymes from all domains of life. It contains 2749 pathways derived from more than 60 000 publications, making it the largest curated collection of metabolic pathways. The data in MetaCyc are evidence-based and richly curated, resulting in an encyclopedic reference tool for metabolism. MetaCyc is also used as a knowledge base for generating thousands of organism-specific Pathway/Genome Databases (PGDBs), which are available in BioCyc.org and other genomic portals. This article provides an update on the developments in MetaCyc during September 2017 to August 2019, up to version 23.1. Some of the topics that received intensive curation during this period include cobamides biosynthesis, sterol metabolism, fatty acid biosynthesis, lipid metabolism, carotenoid metabolism, protein glycosylation, antibiotics and cytotoxins biosynthesis, siderophore biosynthesis, bioluminescence, vitamin K metabolism, brominated compound metabolism, plant secondary metabolism and human metabolism. Other additions include modifications to the GlycanBuilder software that enable displaying glycans using symbolic representation, improved graphics and fonts for web displays, improvements in the PathoLogic component of Pathway Tools, and the optional addition of regulatory information to pathway diagrams.
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
We previously reported on MetaBAT, an automated metagenome binning software tool to reconstruct single genomes from microbial communities for subsequent analyses of uncultivated microbial species. MetaBAT has become one of the most popular binning tools largely due to its computational efficiency and ease of use, especially in binning experiments with a large number of samples and a large assembly. MetaBAT requires users to choose parameters to fine-tune its sensitivity and specificity. If those parameters are not chosen properly, binning accuracy can suffer, especially on assemblies of poor quality. Here, we developed MetaBAT 2 to overcome this problem. MetaBAT 2 uses a new adaptive binning algorithm to eliminate manual parameter tuning. We also performed extensive software engineering optimization to increase both computational and memory efficiency. Comparing MetaBAT 2 to alternative software tools on over 100 real world metagenome assemblies shows superior accuracy and computing speed. Binning a typical metagenome assembly takes only a few minutes on a single commodity workstation. We therefore recommend the community adopts MetaBAT 2 for their metagenome binning experiments. MetaBAT 2 is open source software and available at https://bitbucket.org/berkeleylab/metabat.
Absolute bacterial quantification receives little serious attention in the literature compared to sequencing, conceivably because it is considered unimportant and facile, or because existing methods are tedious, laborious and/or biased in nature. This is particularly true in engineered systems, including activated sludge, where such information underpins their design and operation. To overcome these limitations we built upon existing work and optimised and comprehensively validated, through comparison with epifluorescence microscopy (EFM), a rapid and precise flow cytometric protocol to enumerate total bacterial numbers in activated sludge. Insights into potential biases were evaluated using appropriate statistical analyses on this comparison, which spanned four orders of magnitude, as well as comparing volatile suspended solid (VSS) concentrations. The results suggest flow cytometry (FCM) is a rapid, reproducible and economical technique for quantifying total bacterial numbers and biomass concentrations in activated sludge, despite within order of magnitude discrepancies with EFM counts, which had inherent and evidently greater errors and biases than FCM. The use of FCM for routine monitoring over both EFM and VSS should help further understanding of the microbial ecology in, and the operation of, engineered systems.
In this study, seven full‐scale anaerobic digesters, with or without co‐substrate regime, were analysed by physicochemical and molecular biological methods. A combination of robust community fingerprinting and Illumina MiSeq sequencing revealed a core bacterial community dominated by Chloroflexi, Firmicutes, Bacteroidetes and Proteobacteria, with variations in the profiles because of differences in the co‐substrate feeding regime. Despite these differences, physicochemical properties revealed a stable performance of all reactors, indicating a resilient bacterial microbiota in all full‐scale reactors. A rich bacterial core community ensured reactor functionality, whilst feeding regime and reactor type impacted the overall and the core bacterial diversity. Within the Archaea, Methanosaeta dominated in all reactors. Results indicated no relationship between archaeal community structure and the type of co‐substrate digested. Methanogens rely on the metabolic end products of bacterial activity and are thus less dependent on differences in the initial co‐substrate regime.
Microbial communities are critical to ecosystem function. A key objective of metagenomic studies is to analyse organism-specific metabolic pathways and reconstruct community interaction networks. This requires accurate assignment of assembled genome fragments to genomes. Existing binning methods often fail to reconstruct a reasonable number of genomes and report many bins of low quality and completeness. Furthermore, the performance of existing algorithms varies between samples and biotopes. Here, we present a dereplication, aggregation and scoring strategy, DAS Tool, that combines the strengths of a flexible set of established binning algorithms. DAS Tool applied to a constructed community generated more accurate bins than any automated method. Indeed, when applied to environmental and host-associated samples of different complexity, DAS Tool recovered substantially more near-complete genomes, including previously unreported lineages, than any single binning method alone. The ability to reconstruct many near-complete genomes from metagenomics data will greatly advance genome-centric analyses of ecosystems.
Abstract The 16S ribosomal RNA gene is the most widely used marker gene in microbial ecology. Counts of 16S sequence variants, often in PCR amplicons, are used to estimate proportions of bacterial and archaeal taxa in microbial communities. Because different organisms contain different 16S gene copy numbers (GCNs), sequence variant counts are biased towards clades with greater GCNs. Several tools have recently been developed for predicting GCNs using phylogenetic methods and based on sequenced genomes, in order to correct for these biases. However, the accuracy of those predictions has not been independently assessed. Here, we systematically evaluate the predictability of 16S GCNs across bacterial and archaeal clades, based on ∼ 6,800 public sequenced genomes and using several phylogenetic methods. Further, we assess the accuracy of GCNs predicted by three recently published tools (PICRUSt, CopyRighter, and PAPRICA) over a wide range of taxa and for 635 microbial communities from varied environments. We find that regardless of the phylogenetic method tested, 16S GCNs could only be accurately predicted for a limited fraction of taxa, namely taxa with closely to moderately related representatives (≲15% divergence in the 16S rRNA gene). Consistent with this observation, we find that all considered tools exhibit low predictive accuracy when evaluated against completely sequenced genomes, in some cases explaining less than 10% of the variance. Substantial disagreement was also observed between tools (R 2
In the past few years, many studies investigated the anaerobic digestion microbiome by means of 16S rRNA amplicon sequencing. Results obtained from these studies were compared to each other without taking into consideration the followed procedure for amplicons preparation and data analysis. This negligence was mainly due to the lack of knowledge regarding the biases influencing specific steps of the microbiome investigation process. In the present study, the main technical aspects of the 16S rRNA analysis were checked giving special attention to the approach used for high throughput sequencing. More specifically, the microbial compositions of three laboratory scale biogas reactors were analyzed before and after addition of sodium oleate by sequencing the microbiome with three different approaches: 16S rRNA amplicon sequencing, shotgun DNA and shotgun RNA. This comparative analysis revealed that, in amplicon sequencing, abundance of some taxa (Euryarchaeota and Spirochaetes) was biased by the inefficiency of universal primers to hybridize all the templates. Reliability of the results obtained was also influenced by the number of hypervariable regions under investigation. Finally, amplicon sequencing and shotgun DNA underestimated the Methanoculleus genus, probably due to the low 16S rRNA gene copy number encoded in this taxon.
The MEROPS database (http://www.ebi.ac.uk/merops/) is an integrated source of information about peptidases, their substrates and inhibitors. The hierarchical classification is: protein-species, family, clan, with an identifier at each level. The MEROPS website moved to the EMBL-EBI in 2017, requiring refactoring of the code-base and services provided. The interface to sequence searching has changed and the MEROPS protein sequence libraries can be searched at the EMBL-EBI with HMMER, FastA and BLASTP. Cross-references have been established between MEROPS and the PANTHER database at both the family and protein-species level, which will help to improve curation and coverage between the resources. Because of the increasing size of the MEROPS sequence collection, in future only sequences of characterized proteins, and from completely sequenced genomes of organisms of evolutionary, medical or commercial significance will be added. As an example, peptidase homologues in four proteomes from the Asgard superphylum of Archaea have been identified and compared to other archaean, bacterial and eukaryote proteomes. This has given insights into the origins and evolution of peptidase families, including an expansion in the number of proteasome components in Asgard archaeotes and as organisms increase in complexity. Novel structures for proteasome complexes in archaea are postulated.
Microbial community structure can be analyzed by quantifying cell numbers or by quantifying biomass for individual populations. Methods for quantifying cell numbers are already available (e.g., fluorescence in situ hybridization, 16-S rRNA gene amplicon sequencing), yet high-throughput methods for assessing community structure in terms of biomass are lacking. Here we present metaproteomics-based methods for assessing microbial community structure using protein abundance as a measure for biomass contributions of individual populations. We optimize the accuracy and sensitivity of the method using artificially assembled microbial communities and show that it is less prone to some of the biases found in sequencing-based methods. We apply the method to communities from two different environments, microbial mats from two alkaline soda lakes, and saliva from multiple individuals. We show that assessment of species biomass contributions adds an important dimension to the analysis of microbial community structure.
Challenges in cultivating microorganisms have limited the phylogenetic diversity of currently available microbial genomes. This is being addressed by advances in sequencing throughput and computational techniques that allow for the cultivation-independent recovery of genomes from metagenomes. Here, we report the reconstruction of 7,903 bacterial and archaeal genomes from >1,500 public metagenomes. All genomes are estimated to be ≥50% complete and nearly half are ≥90% complete with ≤5% contamination. These genomes increase the phylogenetic diversity of bacterial and archaeal genome trees by >30% and provide the first representatives of 17 bacterial and three archaeal candidate phyla. We also recovered 245 genomes from the Patescibacteria superphylum (also known as the Candidate Phyla Radiation) and find that the relative diversity of this group varies substantially with different protein marker sets. The scale and quality of this data set demonstrate that recovering genomes from metagenomes provides an expedient path forward to exploring microbial dark matter.The recovery of 7,903 bacterial and archaeal metagenome-assembled genomes increases the phylogenetic diversity represented by public genome repositories and provides the first representatives from 20 candidate phyla.
We present two standards developed by the Genomic Standards Consortium (GSC) for reporting bacterial and archaeal genome sequences. Both are extensions of the Minimum Information about Any (x) Sequence (MIxS). The standards are the Minimum Information about a Single Amplified Genome (MISAG) and the Minimum Information about a Metagenome-Assembled Genome (MIMAG), including, but not limited to, assembly quality, and estimates of genome completeness and contamination. These standards can be used in combination with other GSC checklists, including the Minimum Information about a Genome Sequence (MIGS), Minimum Information about a Metagenomic Sequence (MIMS), and Minimum Information about a Marker Gene Sequence (MIMARKS). Community-wide adoption of MISAG and MIMAG will facilitate more robust comparative genomic analyses of bacterial and archaeal diversity.
While microbes are known to be present at different stages of a drinking water system, their potential functions and ability to grow in such systems are poorly understood. In this study, we demonstrated that treatment and distribution processes could be viewed as ecological disturbances exhibited over space on the microbiome continuum in a groundwater-derived system. Results from 16S rRNA gene amplicon analysis and metagenomics suggested that disturbances in the system were intense as the community diversity was substantially reduced during the treatment steps. Specifically, syntrophs and methanogens dominant in raw water (RW) disappeared after water abstraction, accompanied by a substantial decrease in both the abundance and number of functional genes related to methanogenesis. The softening effluent was dominated by an Exiguobacterium-related population, likely due to its ability to use the phosphotransferase system (PTS) as regulatory machinery to control the energy conditions of the cell. After disinfection and entering the distribution system, community-level functionality remained relatively stable, whereas the community structure differed from those taken in the treatment steps. The diversity and high abundance of some eukaryotic groups in the system suggested that predation could be a disturbance to the bacterial microbiome, which could drive the diversification of the bacterial community. This article is protected by copyright. All rights reserved.
Most Escherichia coli strains live harmlessly in the intestines and rarely cause disease in healthy individuals. Nonetheless, a number of pathogenic strains can cause diarrhea or extraintestinal diseases both in healthy and immunocompromised individuals. Diarrheal illnesses are a severe public health problem and a major cause of morbidity and mortality in infants and young children, especially in developing countries. E. coli strains that cause diarrhea have evolved by acquiring, through horizontal gene transfer, a particular set of characteristics that have successfully persisted in the host. According to the group of virulence determinants acquired, specific combinations were formed determining the currently known E. coli pathotypes, which are collectively known as diarrheagenic E. coli. In this review, we have gathered information on current definitions, serotypes, lineages, virulence mechanisms, epidemiology, and diagnosis of the major diarrheagenic E. coli pathotypes.
Anaerobic digestion is a common technology to biologically stabilize wasted solids produced in municipal wastewater treatment. Its efficiency is usually evaluated by calculating the reduction in volatile solids, which assumes no biomass growth associated with digestion. To determine whether this assumption is valid and further evaluate digestion efficiency, this study sampled 35 digester sludge from different reactors at multiple time points together with the feed biomass in a full-scale water reclamation plant at Chicago, Illinois. The microbial communities were characterized using Illumina sequencing technology based on 16S rRNA and 16S rRNA gene (rDNA). 74 core microbial populations were identified and represented 58.7% of the entire digester community. Among them, active populations were first identified using the ratio of 16S rRNA and 16S rDNA (rRNA/rDNA) for individual populations, but this approach failed to generate consistent results. Subsequently, a recently proposed mass balance model was applied to calculate the specific growth rate (?), and this approach successfully identified active microbial populations in digester (positive ?) that could play important roles than those with negative ?. It was further estimated that 82% of microbial populations in the feed sludge were digested in comparison with less than 50% calculated using current equations.
Understanding the microbial ecology of a system requires that the observed population dynamics can be linked to their metabolic functions. However, functional characterization is laborious and the choice of organisms should be prioritized to those that are frequently abundant (core) or transiently abundant, which are therefore putatively make the greatest contribution to carbon turnover in the system. We analyzed the microbial communities in 13 Danish wastewater treatment plants with nutrient removal in consecutive years and a single plant periodically over 6 years, using Illumina sequencing of 16S ribosomal RNA amplicons of the V4 region. The plants contained a core community of 63 abundant genus-level operational taxonomic units (OTUs) that made up 68% of the total reads. A core community consisting of abundant OTUs was also observed within the incoming wastewater to three plants. The net growth rate for individual OTUs was quantified using mass balance, and it was found that 10% of the total reads in the activated sludge were from slow or non-growing OTUs, and that their measured abundance was primarily because of immigration with the wastewater. Transiently abundant organisms were also identified. Among them the genus Nitrotoga (class Betaproteobacteria) was the most abundant putative nitrite oxidizer in a number of activated sludge plants, which challenges previous assumptions that Nitrospira (phylum Nitrospirae) are the primary nitrite-oxidizers in activated sludge systems with nutrient removal.The ISME Journal advance online publication, 11 August 2015; doi:10.1038/ismej.2015.117.
Both the benefits of bacterial quorum sensing (QS) and cross-feeding for bio-reactor performance in wastewater treatment have been recently reported. As the social traits of microbial communities, how bacterial QS regulating bacterial trade-off by cross-feeding remains unclear. Here, we find diffusion signal factor (DSF), a kind of QS molecules, can bridge bacterial interactions through regulating public goods (extracellular polymeric substances (EPS), amino acids) for metabolic cross-feedings. It showed that exogenous DSF-addition leads to change of public goods level and community structure dynamics in the anammox consortia. Approaches involving meta-omics clarified that anammox and a Lautropia-affiliated species in the phylum Proteobacteria can supply costly public goods for DSF-Secretor species via secondary messenger c-di-GMP regulator (Clp) after sensing DSF. Meanwhile, DSF-Secretor species help anammox bacteria scavenge extracellular detritus, which creates a more suitable environment for the anammox species, enhances the anammox activity, and improves the nitrogen removal rate of anammox reactor. The trade-off induces discrepant metabolic loads of different microbial clusters, which were responsible for the community succession. It illustrated the potential to artificially alleviate metabolic loads for certain bacteria. Deciphering microbial interactions via QS not only provides insights for understanding the social behavior of microbial community, but also creates new thought for enhancing treatment performance through regulating bacterial social traits via quorum sensing-mediated public goods.
A novel, obligately anaerobic bacterium (strain SURF-ANA1 T ) was isolated from deep continental subsurface fluids at a depth of 1500 m below surface in the former Homestake Gold Mine (now Sanford Underground Research Facility, in Lead, South Dakota, USA). Cells of strain SURF-ANA1 T were Gram-negative, helical, non-spore-forming and were 0.25–0.55×5.0–75.0 µm with a wavelength of 0.5–0.62 µm. Strain SURF-ANA1 T grew at 15–50 °C (optimally at 40 °C), at pH 4.8–9.0 (pH 7.2) and in 1.0–40.0 g l ⁻¹ NaCl (10 g l ⁻¹ NaCl). The strain grew chemoheterotrophically with hydrogen or mono-, di- and polysaccharides as electron donors. The major cellular fatty acids in order of decreasing abundance (comprising >5% of total) were 10-methyl C 16:0 , iso-C 15:0 , C 18:2 and C 18:0 dimethyl acetal (DMA) and C 20:0 methylene-nonadecanoic acid. Phylogenetic analysis based on the 16S rRNA gene sequence of strain SURF-ANA1 T indicated a closest relationship with the recently characterized Rectinema cohabitans (99%). Despite high sequence identity, because of its distinct physiology, morphology and fatty acid profile, strain SURF-ANA1 T is considered to represent a novel species within the genus Rectinema , for which the name Rectinema subterraneum sp. nov. is proposed. To our knowledge, this is the first report of an isolate within the phylum Spirochaetes from the deep (>100 m) terrestrial subsurface. The GenBank/EMBL/DDBJ accession numbers for the 16S rRNA gene and genomic sequences of strain SURF-ANA1 T are KU359248 and GCF 009768935.1, respectively. The type strain of Rectinema subterraneum is SURF-ANA1 T (=ATCC TSD-67=JCM 32656).
This study examined the feasibility of cultivation and harvesting of oil-producing microalgae (i.e. Ankistrodesmus falcatus var. acicularis) via biogranulation in two identical sequencing batch reactors (SBRs) fed with synthetic anaerobic digestion liquor. Easily settled algae granules with compact structure appeared around day 90 and mature granules were obtained after 150 days' operation. The microalgae settleability was remarkably improved, signaling by the substantial decrease of sludge volume index (SVI30) from initially >3000 to 53.44 ± 3.31 ml/g, with settling velocity correspondingly increased from nearly 0 to 18.47 ± 0.23 m/h. Although the percentage of the target microalgae (Ankistrodesmus falcatus var. acicularis) decreased along with the granulation process, the biomass concentration (2–4 g/L) and biomass productivity (130–270 mg/L/d) using biogranulation were 10–20 times and 16–34 times that by the traditional suspension method. Compared to the seed microalgae cells, more extracellular polymeric substances (EPS) (162.54 ± 3.60 mg/g-volatile suspended solids (VSS)) with a higher proteins/polysaccharides ratio (7.62) were excreted from the mature algae granules. Moreover, the mature microalgae granules showed comparable nutrients removal, averagely 96% and 86% of dissolved organic carbon (DOC) and NH4⁺-N from the digestion liquor, respectively, reflecting its great potential for simultaneous microalgae cultivation, harvesting and wastewater treatment.
Understanding the bacterial dynamics in cooling towers is imperative for the assessment of disinfection efficiency and management of microbial risks linked to aerosol formation. The objective of this study was to evaluate the impact of feed water on the cooling water bacterial microbiome and investigate the survival ability of its members when exposed to continuous chlorine disinfection. Water from an industrial cooling water system (2600 m3/h) was collected over a 5-month period at 3 locations along the feed water line and 3 locations in the cooling tower. ATP measurements suggested that the average ATP-per-cell in the cooling tower evolved independently from the average ATP-per-cell in the feed water. Flow cytometry and 16S rRNA gene amplicon sequencing were then combined to quantify the bacterial dynamics in the whole system. A mass balance based equation was established to determine net growth and net decay of the cooling tower bacterial communities in order to evaluate the impact of continuous chlorination (0.35-0.41 mg Cl2/L residual chlorine). The results indicated that cooling tower main community members were determined by the input feed water microbiome and the bacterial community structure was further shaped by varying decay rates of the microorganisms. Notably, the order Obscuribacterales showed to be growing in the cooling tower in the presence of residual chlorine up to 0.4 mg Cl2/L, with a recurrent net growth of 260 ± 95%, taking into account the impact of the concentration factor. This conclusion was only possible thanks to the systematic analysis described in this paper and generates discussion about the resistance of Obscuribacterales to residual chlorine. The described mass balance approach provides a high level of understanding on bacterial dynamics and should be considered for future characterization studies of cooling towers in which accurate investigation of microbiome changes is essential.
To determine whether the addition of conductive materials could enhance methane production by direct interspecies electron transfer (DIET), we operated three anaerobic reactors amended with non-conductive (ceramic) or conductive materials (anthracite and granular activated carbon (GAC)). Throughout eight months of operation, ethanol was consistently detected as the major fermentation product. The specific yield in the anthracite and GAC-added reactors increased by 31.5% and 43.3%, respectively, compared to the ceramic-added reactor. 16S rRNA gene sequencing results indicated Geobacter was dominant (up to 55% of total sequences), whereas acids-degrading syntrophic bacteria were low in abundance (<2%). Using metagenomic analysis, the draft genome of the dominant Geobacter population (bin GAC1) was reconstructed and observed to possess genetic abilities of ethanol oxidation, hydrogen production, and extracellular electron transfer, and represented a phylogenetically novel Geobacter species. While Methanosaeta was the dominant methanogen, reactors containing conductive materials harbored more diverse and abundant archaeal populations, as revealed by FISH, qPCR, and metagenomics. Our findings suggested that a novel Geobacter population could oxidize ethanol and employed both hydrogen transfer and DIET depending on the accessibility of conductive materials. Thermodynamic advantages of DIET over hydrogen production could lead to enhanced methane production in reactors with conductive materials.
The number of microbial genomes sequenced each year is expanding rapidly, in part due to genome-resolved metagenomic studies that routinely recover hundreds of draft-quality genomes. Rapid algorithms have been developed to comprehensively compare large genome sets, but they are not accurate with draft-quality genomes. Here we present dRep, a program that reduces the computational time for pairwise genome comparisons by sequentially applying a fast, inaccurate estimation of genome distance, and a slow, accurate measure of average nucleotide identity. dRep achieves a 28 × increase in speed with perfect recall and precision when benchmarked against previously developed algorithms. We demonstrate the use of dRep for genome recovery from time-series datasets. Each metagenome was assembled separately, and dRep was used to identify groups of essentially identical genomes and select the best genome from each replicate set. This resulted in recovery of significantly more and higher-quality genomes compared to the set recovered using co-assembly.
Understanding the influences of biotic and abiotic factors on microbial community structure and methanogenesis are important for its engineering and ecological significance. In this study, four biogas digesters were supplied with the same inoculum and feeding sludge, but operated at different sludge retention time (7 to 16 days) and organic loading rates for 90 days to determine the relative influence of biotic and environmental factors on the microbial community assembly and methanogenic performance. Despite different operational parameters, all digester communities were dominated by Bacteroidales, Clostridiales and Thermotogales, and followed the same trend of population dynamics over time. Network and multivariate analyses suggest that deterministic factors, including microbial competition (involving Bacteroidales spp.), niche differentiation (e.g., within Clostridiales spp.), and periodic microbial immigration (from feed sludge), are the key drivers of microbial community assembly and dynamics. A yet-to-be-cultured phylotype of Bacteroidales (GenBank ID: GU389558.1) is implicated as a strong competitor for carbohydrates. Moreover, biogas-producing rate and methane content were significantly related with the abundances of functional populations rather than any operational or physicochemical parameter, revealing microbiological mediation of methanogenesis. Combined, this study enriches our understandings of biological and environmental drivers of microbial community assembly and performance in anaerobic digesters.
The anaerobic, non-motile strain HMT was isolated from the naphthalene-degrading, sulfate-reducing enrichment culture N47. Since 20 years, strain HMT has been a stable member of culture N47 although it is neither able to degrade naphthalene nor to reduce sulfate in pure culture. The highest similarity of the 16S rRNA gene sequence of strain HMT (89%) is with a cultivated member of the family Spirochaetaceae, Treponema caldarium sp. strain H1T (DSM 7334T), an obligately anaerobic, thermophilic spirochete isolated from cyanobacterial mat samples collected at a freshwater hot spring in Oregon, USA. In contrast to this strain and the majority of described spirochete species, strain HMT showed a rod-shaped morphology. Growth occurred between 12 to 50 °C (optimum 37 °C) but the isolate was not able to grow at 60 °C. The strain fermented various sugars including D-glucose, D-fructose, lactose, and sucrose. Addition of 0.1% (w/v) yeast extract or 0.1% (w/v) tryptone to the culture medium was essential for growth and could neither be replaced by the tested vitamin solutions nor by 0.1% (w/v) peptone or 0.1% (w/v) casamino acids. The DNA G+C content of the isolate was 51.5 mol%. The major fatty acids are C14:0, C18:1ω13c, C16:1ω9t, C16:1ω11c, and C16:1ω9c. Based on the unique morphology and the phylogenetic distance from the closest cultivated relative, a novel genus and species, Rectinema cohabitans gen. nov., sp. nov., is proposed. The type strain is strain HMT (=DSM 100378T =JCM 30982T).
High-throughput amplicon sequencing has become a well-established approach for microbial community profiling. Correlating shifts in the relative abundances of bacterial taxa with environmental gradients is the goal of many microbiome surveys. As the abundances generated by this technology are semi-quantitative by definition, the observed dynamics may not accurately reflect those of the actual taxon densities. We combined the sequencing approach (16S rRNA gene) with robust single-cell enumeration technologies (flow cytometry) to quantify the absolute taxon abundances. A detailed longitudinal analysis of the absolute abundances resulted in distinct abundance profiles that were less ambiguous and expressed in units that can be directly compared across studies. We further provide evidence that the enrichment of taxa (increase in relative abundance) does not necessarily relate to the outgrowth of taxa (increase in absolute abundance). Our results highlight that both relative and absolute abundances should be considered for a comprehensive biological interpretation of microbiome surveys.The ISME Journal advance online publication, 9 September 2016; doi:10.1038/ismej.2016.117.
We present the open-source software package DADA2 for modeling and correcting Illumina-sequenced amplicon errors (https://github.com/benjjneb/dada2). DADA2 infers sample sequences exactly and resolves differences of as little as 1 nucleotide. In several mock communities, DADA2 identified more real variants and output fewer spurious sequences than other methods. We applied DADA2 to vaginal samples from a cohort of pregnant women, revealing a diversity of previously undetected Lactobacillus crispatus variants.
A new strictly anaerobic, short rod-shaped bacterium, designated strain TBC1T, was isolated from methanogenic granular sludge in a full-scale mesophilic upflow anaerobic sludge blanket reactor (UASB) treating high-strength starch-based organic wastewater. The cells were 2-4 µm long and 0.4-0.6 µm in width. They were non-motile and stained Gram-negative. The optimum growth temperature was 30-37℃, with a range of 20 to 40℃. The optimum pH for growth was around pH 7.0, while growth occurred in a range of 6.5-9.0. Strain TBC1T grew chemo-organotrophically on a narrow range of carbohydrates under anaerobic conditions. Yeast extract was required for its growth. The major fermentative end products from glucose, supplemented with yeast extract, were acetate, malate, propionate, formate, and hydrogen. Doubling time under optimal growth conditions was estimated to be one day. The DNA G+C content of strain TBC1T was 49.2 mol% as determined by HPLC. Major cellular fatty acids were C16:0, C18:0, C16:1ω9c, and C18:1ω9c. Based on its 16S rRNA gene sequence, strain TBC1T was shown to represent a distinct lineage at the family level in the phylum Bacteroidetes. Phylogenomic analyses using 38 to 83 single copy marker genes also supported the novelty of strain TBC1T at the family level. Based on its characteristics, we propose that strain TBC1T (JCM 30898T, DSM 100618T) represents a new species of a new genus, namely Lentimicrobium saccharophilum gen. nov., sp. nov. A new family, Lentimicrobiaceae fam. nov., is also proposed encompassing the strain and related environmental 16S rRNA gene clone sequences.
This chapter focuses on the activated sludge (AS) process, which is currently the most widely used biological wastewater treatment process in the developed world. The AS process consists of two separate phases— aeration and sludge settlement. This unit is usually operated with no settlement allowed in the aeration tank, and a completely separate settlement tank with continuous sludge removal. In the first phase, waste-water from the primary settlement tanks is added to the aeration tank containing a mixed microbial population. Air or sometimes pure oxygen is added either by surface agitation or via diffusers using compressed air. The aeration supplies oxygen, for respiration, to the aerobic micro-organisms in the reactor and maintains the microbial flocs in a continuous state of agitated suspension, ensuring maximum contact between the surface of the flocs and the wastewater. The most important function in the AS process is the flocculent nature of the microbial biomass. The flocs not only have to be efficient in the adsorption of and the subsequent absorption of the organic matter in the wastewater, but they also have to be rapidly and effectively separated from the treated effluent within the sedimentation tank. Although some variants of the AS process are used to treat sewage, which has only been screened and degritted, the majority of AS processes use settled sewage as the feedstock.
The recovery of genomes from metagenomic datasets is a critical step to defining the functional roles of the underlying uncultivated populations. We previously developed MaxBin, an automated binning approach for high-throughput recovery of microbial genomes from metagenomes. Here we present an expanded binning algorithm, MaxBin 2.0, which recovers genomes from co-assembly of a collection of metagenomic datasets. Tests on simulated datasets revealed that MaxBin 2.0 is highly accurate in recovering individual genomes, and the application of MaxBin 2.0 to several metagenomes from environmental samples demonstrated that it could achieve two complementary goals: recovering more bacterial genomes compared to binning a single sample as well as comparing the microbial community composition between different sampling environments.
Availability and implementation: MaxBin 2.0 is freely available at http://sourceforge.net/projects/maxbin/ under BSD license.
Contact:ywwei@lbl.gov
Supplementary information:Supplementary data are available at Bioinformatics online.
A protein determination method which involves the binding of Coomassie Brilliant Blue G-250 to protein is described. The binding of the dye to protein causes a shift in the absorption maximum of the dye from 465 to 595 nm, and it is the increase in absorption at 595 nm which is monitored. This assay is very reproducible and rapid with the dye binding process virtually complete in approximately 2 min with good color stability for 1 hr. There is little or no interference from cations such as sodium or potassium nor from carbohydrates such as sucrose. A small amount of color is developed in the presence of strongly alkaline buffering agents, but the assay may be run accurately by the use of proper buffer controls. The only components found to give excessive interfering color in the assay are relatively large amounts of detergents such as sodium dodecyl sulfate, Triton X-100, and commercial glassware detergents. Interference by small amounts of detergent may be eliminated by the use of proper controls.
Drinking water distribution systems (DWDSs) harbor the microorganisms in biofilms and suspended communities, yet the diversity and spatiotemporal distribution have been studied mainly in the suspended communities. This study examined the diversity of biofilms in an urban DWDS, its relationship with suspended communities and its dynamics. The studied DWDS in Urbana, Illinois received conventionally treated and disinfected water sourced from the groundwater. Over a 2-year span, biomass were sampled from household water meters (n=213) and tap water (n=20) to represent biofilm and suspended communities, respectively. A positive correlation between operational taxonomic unit (OTU) abundance and occupancy was observed. Examined under a 'core-satellite' model, the biofilm community comprised 31 core populations that encompassed 76.7% of total 16 S rRNA gene pyrosequences. The biofilm communities shared with the suspended community highly abundant and prevalent OTUs, which related to methano-/methylotrophs (i.e., Methylophilaceae and Methylococcaceae) and aerobic heterotrophs (Sphingomonadaceae and Comamonadaceae), yet differed by specific core populations and lower diversity and evenness. Multivariate tests indicated seasonality as the main contributor to community structure variation. This pattern was resilient to annual change and correlated to the cyclic fluctuations of core populations. The findings of a distinctive biofilm community assemblage and methano-/methyltrophic primary production provide critical insights for developing more targeted water quality monitoring programs and treatment strategies for groundwater-sourced drinking water systems.The ISME Journal advance online publication, 7 August 2015; doi:10.1038/ismej.2015.136.