ASM-Clust: classifying functionally diverse protein families using alignment score matrices

Rapid advances in sequencing technology have resulted in the availability of genomes from organisms across the tree of life. Accurately interpreting the function of proteins in these genomes is a major challenge, as annotation transfer based on homology frequently results in misannotation and error propagation. This challenge is especially pressing for organisms whose genomes are directly obtained from environmental samples, as interpretation of their physiology and ecology is often based solely on the genome sequence. For complex protein (super)families containing a large number of sequences, classification can be used to determine whether annotation transfer is appropriate, or whether experimental evidence for function is lacking. Here we present a novel computational approach for de novo classification of large protein (super)families, based on clustering an alignment score matrix obtained by aligning all sequences in the family to a small subset of the data. We evaluate our approach on the enolase family in the Structure Function Linkage Database

Metabolic marker gene mining provides insight in global mcrA diversity and, coupled with targeted genome reconstruction, sheds further light on metabolic potential of the Methanomassiliicoccales

Over the past years, metagenomics has revolutionized our view of microbial diversity. Moreover, extracting near-complete genomes from metagenomes has led to the discovery of known metabolic traits in unsuspected lineages. Genome-resolved metagenomics relies on assembly of the sequencing reads and subsequent binning of assembled contigs, which might be hampered by strain heterogeneity or low abundance of a target organism. Here we present a complementary approach, metagenome marker gene mining, and use it to assess the global diversity of archaeal methane metabolism through the mcrA gene. To this end, we have screened 18,465 metagenomes for the presence of reads matching a database representative of all known mcrA proteins and reconstructed gene sequences from the matching reads. We use our mcrA dataset to assess the environmental distribution of the Methanomassiliicoccales and reconstruct and analyze a draft genome belonging to the ‘Lake Pavin cluster’, an uncultivated environmental clade of the Methanomassiliicoccales. Analysis of the ‘Lake Pavin cluster’ draft genome suggests that this organism has a more restricted capacity for hydrogenotrophic methylotrophic methanogenesis than previously studied Methanomassiliicoccales, with only genes for growth on methanol present. However, the presence of the soluble subunits of methyltetrahydromethanopterin:CoM methyltransferase (mtrAH) provide hypothetical pathways for methanol fermentation, and aceticlastic methanogenesis that await experimental verification. Thus, we show that marker gene mining can enhance the discovery power of metagenomics, by identifying novel lineages and aiding selection of targets for in-depth analyses. Marker gene mining is less sensitive to strain heterogeneity and has a lower abundance threshold than genome-resolved metagenomics, as it only requires short contigs and there is no binning step. Additionally, it is computationally cheaper than genome resolved metagenomics, since only a small subset of reads needs to be assembled. It is therefore a suitable approach to extract knowledge from the many publicly available sequencing projects

ASM-Clust: classifying functionally diverse protein families using alignment score matrices

Rapid advances in sequencing technology have resulted in the availability of genomes from organisms across the tree of life. Accurately interpreting the function of proteins in these genomes is a major challenge, as annotation transfer based on homology frequently results in misannotation and error propagation. This challenge is especially pressing for organisms whose genomes are directly obtained from environmental samples, as interpretation of their physiology and ecology is often based solely on the genome sequence. For complex protein (super)families containing a large number of sequences, classification can be used to determine whether annotation transfer is appropriate, or whether experimental evidence for function is lacking. Here we present a novel computational approach for de novo classification of large protein (super)families, based on clustering an alignment score matrix obtained by aligning all sequences in the family to a small subset of the data. We evaluate our approach on the enolase family in the Structure Function Linkage Database

Metabolic marker gene mining provides insight in global mcrA diversity and, coupled with targeted genome reconstruction, sheds further light on metabolic potential of the Methanomassiliicoccales

Over the past years, metagenomics has revolutionized our view of microbial diversity. Moreover, extracting near-complete genomes from metagenomes has led to the discovery of known metabolic traits in unsuspected lineages. Genome-resolved metagenomics relies on assembly of the sequencing reads and subsequent binning of assembled contigs, which might be hampered by strain heterogeneity or low abundance of a target organism. Here we present a complementary approach, metagenome marker gene mining, and use it to assess the global diversity of archaeal methane metabolism through the mcrA gene. To this end, we have screened 18,465 metagenomes for the presence of reads matching a database representative of all known mcrA proteins and reconstructed gene sequences from the matching reads. We use our mcrA dataset to assess the environmental distribution of the Methanomassiliicoccales and reconstruct and analyze a draft genome belonging to the ‘Lake Pavin cluster’, an uncultivated environmental clade of the Methanomassiliicoccales. Analysis of the ‘Lake Pavin cluster’ draft genome suggests that this organism has a more restricted capacity for hydrogenotrophic methylotrophic methanogenesis than previously studied Methanomassiliicoccales, with only genes for growth on methanol present. However, the presence of the soluble subunits of methyltetrahydromethanopterin:CoM methyltransferase (mtrAH) provide hypothetical pathways for methanol fermentation, and aceticlastic methanogenesis that await experimental verification. Thus, we show that marker gene mining can enhance the discovery power of metagenomics, by identifying novel lineages and aiding selection of targets for in-depth analyses. Marker gene mining is less sensitive to strain heterogeneity and has a lower abundance threshold than genome-resolved metagenomics, as it only requires short contigs and there is no binning step. Additionally, it is computationally cheaper than genome resolved metagenomics, since only a small subset of reads needs to be assembled. It is therefore a suitable approach to extract knowledge from the many publicly available sequencing projects

Archaea catalyze iron-dependent anaerobic oxidation of methane

Anaerobic oxidation of methane (AOM) is crucial for controlling the emission of this potent greenhouse gas to the atmosphere. Nitrite-, nitrate-, and sulfate-dependent methane oxidation is well-documented, but AOM coupled to the reduction of oxidized metals has so far been demonstrated only in environmental samples. Here, using a freshwater enrichment culture, we show that archaea of the order Methanosarcinales, related to “Candidatus Methanoperedens nitroreducens,” couple the reduction of environmentally relevant forms of Fe^(3+) and Mn^(4+) to the oxidation of methane. We obtained an enrichment culture of these archaea under anaerobic, nitrate-reducing conditions with a continuous supply of methane. Via batch incubations using [^(13)C]methane, we demonstrated that soluble ferric iron (Fe^(3+), as Fe-citrate) and nanoparticulate forms of Fe^(3+) and Mn^(4+) supported methane-oxidizing activity. CO_2 and ferrous iron (Fe^(2+)) were produced in stoichiometric amounts. Our study connects the previous finding of iron-dependent AOM to microorganisms detected in numerous habitats worldwide. Consequently, it enables a better understanding of the interaction between the biogeochemical cycles of iron and methane

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

Thermotogota diversity and distribution patterns revealed in Auka and JaichMaa ja ag hydrothermal vent fields in the Pescadero Basin, Gulf of California.

Discovering new deep hydrothermal vent systems is one of the biggest challenges in ocean exploration. They are a unique window to elucidate the physical, geochemical, and biological processes that occur on the seafloor and are involved in the evolution of life on Earth. In this study, we present a molecular analysis of the microbial composition within the newly discovered hydrothermal vent field, JaichMaa ja ag, situated in the Southern Pescadero Basin within the Gulf of California. During the cruise expedition FK181031 in 2018, 33 sediment cores were collected from various sites within the Pescadero vent fields and processed for 16S rRNA amplicon sequence variants (ASVs) and geochemical analysis. Correlative analysis of the chemical composition of hydrothermal pore fluids and microbial abundances identified several sediment-associated phyla, including Thermotogota, that appear to be enriched in sediment horizons impacted by hydrothermal fluid flow. Comparative analysis of Thermotogota with the previously explored Auka hydrothermal vent field situated 2 km away displayed broad similarity between the two locations, although at finer scales (e.g., ASV level), there were notable differences that point to core-to-core and site-level factors revealing distinct patterns of distribution and abundance within these two sediment-hosted hydrothermal vent fields. These patterns are intricately linked to the specific physical and geochemical conditions defining each vent, illuminating the complexity of this unique deep ocean chemosynthetic ecosystem

A novel mesocosm set-up reveals strong methane emission reduction in submerged peat moss Sphagnum cuspidatum by tightly associated methanotrophs

Wetlands present the largest natural sources of methane (CH_4) and their potential CH_4 emissions greatly vary due to the activity of CH_4-oxidizing bacteria associated with wetland plant species. In this study, the association of CH_4-oxidizing bacteria with submerged Sphagnum peat mosses was studied, followed by the development of a novel mesocosm set-up. This set-up enabled the precise control of CH_4 input and allowed for monitoring the dissolved CH_4in a Sphagnum moss layer while mimicking natural conditions. Two mesocosm set-ups were used in parallel: one containing a Sphagnum moss layer in peat water, and a control only containing peat water. Moss-associated CH_4 oxidizers in the field could reduce net CH_4 emission up to 93%, and in the mesocosm set-up up to 31%. Furthermore, CH_4 oxidation was only associated with Sphagnum, and did not occur in peat water. Especially methanotrophs containing a soluble methane monooxygenase enzyme were significantly enriched during the 32 day mesocosm incubations. Together these findings showed the new mesocosm setup is very suited to study CH_4 cycling in submerged Sphagnum moss community under controlled conditions. Furthermore, the tight associated between Sphagnum peat mosses and methanotrophs can significantly reduce CH_4 emissions in submerged peatlands