Chemosynthetic symbioses are partnerships between invertebrate animals and chemosynthetic bacteria. The latter are the primary producers, providing most of the organic carbon needed for the animal host's nutrition. We sequenced genomes of the chemosynthetic symbionts from the lucinid bivalve Loripes lucinalis and the stilbonematid nematode Laxus oneistus. The symbionts of both host species encoded nitrogen fixation genes. This is remarkable as no marine chemosynthetic symbiont was previously known to be capable of nitrogen fixation. We detected nitrogenase expression by the symbionts of lucinid clams at the transcriptomic and proteomic level. Mean stable nitrogen isotope values of Loripes lucinalis were within the range expected for fixed atmospheric nitrogen, further suggesting active nitrogen fixation by the symbionts. The ability to fix nitrogen may be widespread among chemosynthetic symbioses in oligotrophic habitats, where nitrogen availability often limits primary productivity.S ymbioses between animals and chemosynthetic bacteria are widespread in Earth's oceans 1 . Animals from at least seven phyla have formed such symbioses, and even more chemosynthetic bacterial lineages have evolved symbioses with animal hosts 1 . Chemosynthetic symbionts can use a range of chemicals, such as sulfide, methane, hydrogen and carbon monoxide, to power their metabolism 2-4 . The hosts of chemosynthetic symbionts dominate some animal communities. For example, shallow-water lucinid bivalves, which host sulfur-oxidizing symbionts, often dominate the macrobenthic infaunal community in seagrass meadows, where they can reach densities greater than 3,500 individuals per square metre 5,6 . Their diversity in nature, their persistence over evolutionary timescales and their dominance in many habitats attest to the success of these symbiotic partnerships 1 .Chemosynthetic symbionts are primarily considered 'nutritional symbionts', meaning their primary role is to provide nutrition for their hosts 1,7 . So far, most studies have focused on inorganic carbon fixation by the symbionts and the transfer of fixed organic carbon compounds to the hosts. In addition to organic carbon, all animals require a source of fixed nitrogen. However, nitrogen metabolism in chemosynthetic symbioses has received far less attention. Chemosynthetic symbionts have been shown to gain their nitrogen from ammonium or nitrate in their environment 8-10 and co-occurring nitrogen-fixing and chemosynthetic symbionts have been found in cold-water corals 11 . Nitrogen fixation by chemosynthetic symbionts has long been hypothesized, but so far not yet shown [12][13][14] .Our study focused mainly on the endosymbiosis between bivalves of the family Lucinidae and sulfur-oxidizing bacteria. Lucinids are by far the most diverse and widespread group of bivalves that host chemosynthetic symbionts 15 . There are at least 400 living species, occupying a range of habitats including mangrove sediments, seagrass beds, coral reef sediments and coastal mud and sand 16 . In seagrass...
The small-subunit rRNA (SSU rRNA) gene is the key marker in molecular ecology for all domains of life, but it is largely absent from metagenome-assembled genomes that often are the only resource available for environmental microbes. Here, we present phyloFlash, a pipeline to overcome this gap with rapid, SSU rRNA-centered taxonomic classification, targeted assembly, and graph-based binning of full metagenomic assemblies. We show that a cleanup of artifacts is pivotal even with a curated reference database. With such a filtered database, the general-purpose mapper BBmap extracts SSU rRNA reads five times faster than the rRNA-specialized tool SortMeRNA with similar sensitivity and higher selectivity on simulated metagenomes. Reference-based targeted assemblers yielded either highly fragmented assemblies or high levels of chimerism, so we employ the general-purpose genomic assembler SPAdes. Our optimized implementation is independent of reference database composition and has satisfactory levels of chimera formation. phyloFlash quickly processes Illumina (meta)genomic data, is straightforward to use, even as part of high-throughput quality control, and has user-friendly output reports. The software is available at https://github.com/HRGV/phyloFlash (GPL3 license) and is documented with an online manual. IMPORTANCE To track organisms across all domains of life, the SSU rRNA gene is the gold standard. Many environmental microbes are known only from high-throughput sequence data, but the SSU rRNA gene, the key to visualization by molecular probes and link to existing literature, is often missing from metagenome-assembled genomes (MAGs). The easy-to-use phyloFlash software suite tackles this gap with rapid, SSU rRNA-centered taxonomic classification, targeted assembly, and graph-based linking to MAGs. Starting from a cleaned reference database, phyloFlash profiles the taxonomic diversity and assembles the sorted SSU rRNA reads. The phyloFlash design is domain agnostic and covers eukaryotes, archaea, and bacteria alike. phyloFlash also provides utilities to visualize multisample comparisons and to integrate the recovered SSU rRNAs in a metagenomics workflow by linking them to MAGs using assembly graph parsing.
The SSU rRNA gene is the key marker in molecular ecology for all domains of life, but is largely absent from metagenome-assembled genomes that often are the only resource available for environmental microbes. Here we present phyloFlash, a pipeline to overcome this gap with rapid, SSU rRNA-centered taxonomic classification, targeted assembly, and graph-based binning of full metagenomic assemblies. We show that a cleanup of artifacts is pivotal even with a curated reference database. With such a filtered database, the general-purpose mapper BBmap extracts SSU rRNA reads five times faster than the rRNA-specialized tool SortMeRNA with similar sensitivity and higher selectivity on simulated metagenomes. Reference-based targeted assemblers yielded either highly fragmented assemblies or high levels of chimerism, so we employ the general-purpose genomic assembler SPAdes. Our optimized implementation is independent of reference database composition and has satisfactory levels of chimera formation. Using the phyloFlash workflow we could recover the first complete genomes of several enigmatic taxa, including Marinamargulisbacteria from surface ocean seawater. phyloFlash quickly processes Illumina (meta)genomic data, is straightforward to use, even as part of high-throughput quality control, and has user-friendly output reports. The software is available at https://github.com/HRGV/phyloFlash (GPL3 license) and is documented with an online manual.reads (12)(13)(14), and some tools also go beyond classification to perform targeted assembly of specific genes (15,16). Regardless of the method that is used for taxonomic or functional profiling, the results will be limited by the reference data available. For example, target organisms or their close relatives may not yet be represented in the database, and horizontal gene transfer can result in conflicting phylogenetic signal, especially in prokaryotic microbes (17,18).In molecular ecology, the gene for the small subunit ribosomal RNA (SSU rRNA) is the most important marker because it can be readily used to link sequences to actual cells. The SSU rRNA is available in high copy numbers in ribosomes and can be accessed through the well-established molecular probing technique of fluorescence in situ hybridization (FISH) (19, 20) Its value in imaging based analyses together with its high phylogenetic reliability due to low rates of horizontal transfer has made the SSU rRNA gene the best-sampled marker in terms of phylogenetic diversity (21). Even with the current advances of metagenomics, where drafts of microbial genomes can automatically project (https://www.arb-silva.de) (28). Sequences containing fragments of the large subunit (LSU) rRNA are detected with a hidden Markov model (HMM) from a customized version of Barrnap (Evalue cutoff 10 -10 , >10% of total model length) (https://github.com/tseemann/barrnap), and are removed. Sequence regions containing low-complexity sequence or repeat k-mers are masked with bbmask.sh (from BBmap, https://sourceforge.net/projects/bbmap/) using k-m...
Improvements in DNA sequencing technology have increased the amount and quality of sequences that can be obtained from metagenomic samples, making it practical to extract individual microbial genomes from metagenomic assemblies (“binning”). However, while many tools and methods exist for unsupervised binning with various statistical algorithms, there are few options for visualizing the results, even though visualization is vital to exploratory data analysis. We have developed gbtools, a software package that allows users to visualize metagenomic assemblies by plotting coverage (sequencing depth) and GC values of contigs, and also to annotate the plots with taxonomic information. Different sets of annotations, including taxonomic assignments from conserved marker genes or SSU rRNA genes, can be imported simultaneously; users can choose which annotations to plot. Bins can be manually defined from plots, or be imported from third-party binning tools and overlaid onto plots, such that results from different methods can be compared side-by-side. gbtools reports summary statistics of bins including marker gene completeness, and allows the user to add or subtract bins with each other. We illustrate some of the functions available in gbtools with two examples: the metagenome of Olavius algarvensis, a marine oligochaete worm that has up to five bacterial symbionts, and the metagenome of a synthetic mock community comprising 64 bacterial and archaeal strains. We show how instances of poor automated binning, sequencer GC% bias, and variation between samples can be quickly diagnosed by visualization, and demonstrate how the results from different binning tools can be combined and refined to yield manually curated bins with higher completeness. gbtools is open-source and written in R. The software package, documentation, and example data are available freely online at https://github.com/kbseah/genome-bin-tools.
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