Evaluating metagenomics tools for genome binning with real metagenomic datasets and CAMI datasets

Background

Shotgun metagenomics based on untargeted sequencing can explore the taxonomic profile and the function of unknown microorganisms in samples, and complement the shortage of amplicon sequencing. Binning assembled sequences into individual groups, which represent microbial genomes, is the key step and a major challenge in metagenomic research. Both supervised and unsupervised machine learning methods have been employed in binning. Genome binning belonging to unsupervised method clusters contigs into individual genome bins by machine learning methods without the assistance of any reference databases. So far a lot of genome binning tools have emerged. Evaluating these genome tools is of great significance to microbiological research. In this study, we evaluate 15 genome binning tools containing 12 original binning tools and 3 refining binning tools by comparing the performance of these tools on chicken gut metagenomic datasets and the first CAMI challenge datasets.

Results

For chicken gut metagenomic datasets, original genome binner MetaBat, Groopm2 and Autometa performed better than other original binner, and MetaWrap combined the binning results of them generated the most high-quality genome bins. For CAMI datasets, Groopm2 achieved the highest purity (> 0.9) with good completeness (> 0.8), and reconstructed the most high-quality genome bins among original genome binners. Compared with Groopm2, MetaBat2 had similar performance with higher completeness and lower purity. Genome refining binners DASTool predicated the most high-quality genome bins among all genomes binners. Most genome binner performed well for unique strains. Nonetheless, reconstructing common strains still is a substantial challenge for all genome binner.

Conclusions

In conclusion, we tested a set of currently available, state-of-the-art metagenomics hybrid binning tools and provided a guide for selecting tools for metagenomic binning by comparing range of purity, completeness, adjusted rand index, and the number of high-quality reconstructed bins. Furthermore, available information for future binning strategy were concluded.

CAMISIM: simulating metagenomes and microbial communities

BACKGROUND

Shotgun metagenome data sets of microbial communities are highly diverse, not only due to the natural variation of the underlying biological systems, but also due to differences in laboratory protocols, replicate numbers, and sequencing technologies. Accordingly, to effectively assess the performance of metagenomic analysis software, a wide range of benchmark data sets are required.

RESULTS

We describe the CAMISIM microbial community and metagenome simulator. The software can model different microbial abundance profiles, multi-sample time series, and differential abundance studies, includes real and simulated strain-level diversity, and generates second- and third-generation sequencing data from taxonomic profiles or de novo. Gold standards are created for sequence assembly, genome binning, taxonomic binning, and taxonomic profiling. CAMSIM generated the benchmark data sets of the first CAMI challenge. For two simulated multi-sample data sets of the human and mouse gut microbiomes, we observed high functional congruence to the real data. As further applications, we investigated the effect of varying evolutionary genome divergence, sequencing depth, and read error profiles on two popular metagenome assemblers, MEGAHIT, and metaSPAdes, on several thousand small data sets generated with CAMISIM.

CONCLUSIONS

CAMISIM can simulate a wide variety of microbial communities and metagenome data sets together with standards of truth for method evaluation. All data sets and the software are freely available at https://github.com/CAMI-challenge/CAMISIM.

Assembling a genome for novel nitrogen-fixing bacteria with capabilities for utilization of aromatic hydrocarbons

Metagenome from refinery wastewater treatment plant running under nitrogen stress was analyzed for mining of novel aromatic hydrocarbon-degrading bacteria. The sequence data were assembled using metaspade followed by binning using the Metabat tool to assemble genome; where coverage and depth were calculated using bowtie and samtools. The analysis picked a novel genome belonging to family Bradyrhizobiaceae, identified based on 16S rDNA gene which was supported by CheckM and Kraken analysis. Using RAST, the assembled genome showed the capabilities for nitrogen fixation with the utilization of multiple hydrocarbon substrates with 14 different types of oxygenases as mapped by Minpath. An additional genetic feature like genes for stress and resistance towards heavy metals and antibiotic suggested that the genome has gone through the rigorous process of adaptation. If such bacteria could be cultivated then it will open the broad window of bioremediation strategies under nitrogen stress environment.

Genome-resolved metagenomics of sugarcane vinasse bacteria

BACKGROUND

The production of 1 L of ethanol from sugarcane generates up to 12 L of vinasse, which is a liquid waste containing an as-yet uncharacterized microbial assemblage. Most vinasse is destined for use as a fertilizer on the sugarcane fields because of the high organic and K content; however, increased N₂O emissions have been observed when vinasse is co-applied with inorganic N fertilizers. Here we aimed to characterize the microbial assemblage of vinasse to determine the gene potential of vinasse microbes for contributing to negative environmental effects during fertirrigation and/or to the obstruction of bioethanol fermentation.

RESULTS

We measured chemical characteristics and extracted total DNA from six vinasse batches taken over 1.5 years from a bioethanol and sugar mill in Sao Paulo State. The vinasse microbial assemblage was characterized by low alpha diversity with 5-15 species across the six vinasses. The core genus was Lactobacillus. The top six represented bacterial genera across the samples were Lactobacillus, Megasphaera and Mitsuokella (Phylum Firmicutes, 35-97% of sample reads); Arcobacter and Alcaligenes (Phylum Proteobacteria, 0-40%); Dysgonomonas (Phylum Bacteroidetes, 0-53%); and Bifidobacterium (Phylum Actinobacteria, 0-18%). Potential genes for denitrification but not nitrification were identified in the vinasse metagenomes, with putative nirK and nosZ genes the most represented. Binning resulted in 38 large bins with between 36.0 and 99.3% completeness, and five small mobile element bins. Of the large bins, 53% could be classified at the phylum level as Firmicutes, 15% as Proteobacteria, 13% as unknown phyla, 13% as Bacteroidetes and 6% as Actinobacteria. The large bins spanned a range of potential denitrifiers; moreover, the genetic repertoires of all the large bins included the presence of genes involved in acetate, CO₂, ethanol, H₂O₂, and lactose metabolism; for many of the large bins, genes related to the metabolism of mannitol, xylose, butyric acid, cellulose, sucrose, "3-hydroxy" fatty acids and antibiotic resistance were present based on the annotations. In total, 21 vinasse bacterial draft genomes were submitted to the genome repository.

CONCLUSIONS

Identification of the gene repertoires of vinasse bacteria and assemblages supported the idea that organic carbon and nitrogen present in vinasse together with microbiological variation of vinasse might lead to varying patterns of N₂O emissions during fertirrigation. Furthermore, we uncovered draft genomes of novel strains of known bioethanol contaminants, as well as draft genomes unknown at the phylum level. This study will aid efforts to improve bioethanol production efficiency and sugarcane agriculture sustainability.

Characterization of Bathyarchaeota genomes assembled from metagenomes of biofilms residing in mesophilic and thermophilic biogas reactors

BACKGROUND

Previous studies on the Miscellaneous Crenarchaeota Group, recently assigned to the novel archaeal phylum Bathyarchaeota, reported on the dominance of these Archaea within the anaerobic carbohydrate cycle performed by the deep marine biosphere. For the first time, members of this phylum were identified also in mesophilic and thermophilic biogas-forming biofilms and characterized in detail.

RESULTS

Metagenome shotgun libraries of biofilm microbiomes were sequenced using the Illumina MiSeq system. Taxonomic classification revealed that between 0.1 and 2% of all classified sequences were assigned to Bathyarchaeota. Individual metagenome assemblies followed by genome binning resulted in the reconstruction of five metagenome-assembled genomes (MAGs) of Bathyarchaeota. MAGs were estimated to be 65-92% complete, ranging in their genome sizes from 1.1 to 2.0 Mb. Phylogenetic classification based on core gene sets confirmed their placement within the phylum Bathyarchaeota clustering as a separate group diverging from most of the recently known Bathyarchaeota clusters. The genetic repertoire of these MAGs indicated an energy metabolism based on carbohydrate and amino acid fermentation featuring the potential for extracellular hydrolysis of cellulose, cellobiose as well as proteins. In addition, corresponding transporter systems were identified. Furthermore, genes encoding enzymes for the utilization of carbon monoxide and/or carbon dioxide via the Wood-Ljungdahl pathway were detected.

CONCLUSIONS

For the members of Bathyarchaeota detected in the biofilm microbiomes, a hydrolytic lifestyle is proposed. This is the first study indicating that Bathyarchaeota members contribute presumably to hydrolysis and subsequent fermentation of organic substrates within biotechnological biogas production processes.

Draft Genome of Scalindua rubra, Obtained from the Interface Above the Discovery Deep Brine in the Red Sea, Sheds Light on Potential Salt Adaptation Strategies in Anammox Bacteria

Several recent studies have indicated that members of the phylum Planctomycetes are abundantly present at the brine-seawater interface (BSI) above multiple brine pools in the Red Sea. Planctomycetes include bacteria capable of anaerobic ammonium oxidation (anammox). Here, we investigated the possibility of anammox at BSI sites using metagenomic shotgun sequencing of DNA obtained from the BSI above the Discovery Deep brine pool. Analysis of sequencing reads matching the 16S rRNA and hzsA genes confirmed presence of anammox bacteria of the genus Scalindua. Phylogenetic analysis of the 16S rRNA gene indicated that this Scalindua sp. belongs to a distinct group, separate from the anammox bacteria in the seawater column, that contains mostly sequences retrieved from high-salt environments. Using coverage- and composition-based binning, we extracted and assembled the draft genome of the dominant anammox bacterium. Comparative genomic analysis indicated that this Scalindua species uses compatible solutes for osmoadaptation, in contrast to other marine anammox bacteria that likely use a salt-in strategy. We propose the name Candidatus Scalindua rubra for this novel species, alluding to its discovery in the Red Sea.

Identification and genome reconstruction of abundant distinct taxa in microbiomes from one thermophilic and three mesophilic production-scale biogas plants

BACKGROUND

Biofuel production from conversion of biomass is indispensable in the portfolio of renewable energies. Complex microbial communities are involved in the anaerobic digestion process of plant material, agricultural residual products and food wastes. Analysis of the genetic potential and microbiology of communities degrading biomass to biofuels is considered to be the key to develop process optimisation strategies. Hence, due to the still incomplete taxonomic and functional characterisation of corresponding communities, new and unknown species are of special interest.

RESULTS

Three mesophilic and one thermophilic production-scale biogas plants (BGPs) were taxonomically profiled using high-throughput 16S rRNA gene amplicon sequencing. All BGPs shared a core microbiome with the thermophilic BGP featuring the lowest diversity. However, the phyla Cloacimonetes and Spirochaetes were unique to BGPs 2 and 3, Fusobacteria were only found in BGP3 and members of the phylum Thermotogae were present only in the thermophilic BGP4. Taxonomic analyses revealed that these distinctive taxa mostly represent so far unknown species. The only exception is the dominant Thermotogae OTU featuring 16S rRNA gene sequence identity to Defluviitoga tunisiensis L3, a sequenced and characterised strain. To further investigate the genetic potential of the biogas communities, corresponding metagenomes were sequenced in a deepness of 347.5 Gbp in total. A combined assembly comprised 80.3 % of all reads and resulted in the prediction of 1.59 million genes on assembled contigs. Genome binning yielded genome bins comprising the prevalent distinctive phyla Cloacimonetes, Spirochaetes, Fusobacteria and Thermotogae. Comparative genome analyses between the most dominant Thermotogae bin and the very closely related Defluviitoga tunisiensis L3 genome originating from the same BGP revealed high genetic similarity. This finding confirmed applicability and reliability of the binning approach. The four highly covered genome bins of the other three distinct phyla showed low or very low genetic similarities to their closest phylogenetic relatives, and therefore indicated their novelty.

CONCLUSIONS

In this study, the 16S rRNA gene sequencing approach and a combined metagenome assembly and binning approach were used for the first time on different production-scale biogas plants and revealed insights into the genetic potential and functional role of so far unknown species.

Anvi'o: an advanced analysis and visualization platform for 'omics data

Advances in high-throughput sequencing and ‘omics technologies are revolutionizing studies of naturally occurring microbial communities. Comprehensive investigations of microbial lifestyles require the ability to interactively organize and visualize genetic information and to incorporate subtle differences that enable greater resolution of complex data. Here we introduce anvi’o, an advanced analysis and visualization platform that offers automated and human-guided characterization of microbial genomes in metagenomic assemblies, with interactive interfaces that can link ‘omics data from multiple sources into a single, intuitive display. Its extensible visualization approach distills multiple dimensions of information about each contig, offering a dynamic and unified work environment for data exploration, manipulation, and reporting. Using anvi’o, we re-analyzed publicly available datasets and explored temporal genomic changes within naturally occurring microbial populations through de novo characterization of single nucleotide variations, and linked cultivar and single-cell genomes with metagenomic and metatranscriptomic data. Anvi’o is an open-source platform that empowers researchers without extensive bioinformatics skills to perform and communicate in-depth analyses on large ‘omics datasets.