Recovery of strain-resolved genomes from human microbiome through an integration framework of single-cell genomics and metagenomics

Background Obtaining high-quality (HQ) reference genomes from microbial communities is crucial for understanding the phylogeny and function of uncultured microbes in complex microbial ecosystems. Despite improvements in bioinformatic approaches to generate curated metagenome-assembled genomes (MAGs), existing metagenome binners obtain population consensus genomes but they are nowhere comparable to genomes sequenced from isolates in terms of strain level resolution. Here, we present a framework for the integration of single-cell genomics and metagenomics, referred to as single-cell (sc) metagenomics, to reconstruct strain-resolved genomes from microbial communities at once. Results Our sc-metagenomics integration framework, termed SMAGLinker, uses single-cell amplified genomes (SAGs) generated using microfluidic technology as binning guides and integrates them with metagenome-assembled genomes (MAGs) to recover improved draft genomes. We compared sc-metagenomics with the metagenomics-alone approach using conventional metagenome binners. The sc-metagenomics approach showed precise contig binning and higher recovery rates (>97%) of rRNA and plasmids than conventional metagenomics in genome reconstruction from the cell mock community. In human microbiota samples, sc-metagenomics recovered the largest number of genomes with a total of 103 gut microbial genomes (21 HQ, with 65 showing >90% completeness) and 45 skin microbial genomes (10 HQ, with 40 showing >90% completeness), respectively. Conventional metagenomics recovered one Staphylococcus hominis genome, whereas sc-metagenomics recovered two S. hominis genomes from identical skin microbiota sample. Single-cell sequencing revealed that these S. hominis genomes were derived from two distinct strains harboring specifically different plasmids. We found that all conventional S. hominis MAGs had a substantial lack or excess of genome sequences and contamination from other Staphylococcus species (S. epidermidis). Conclusions SMAGLinker enabled us to obtain strain-resolved genomes in the mock community and human microbiota samples by assigning metagenomic sequences correctly and covering both highly conserved genes such as rRNA genes and unique extrachromosomal elements, including plasmids. SMAGLinker will provide HQ genomes that are difficult to obtain using metagenomics alone and will facilitate the understanding of microbial ecosystems by elucidating detailed metabolic pathways and horizontal gene transfer networks. SMAGLinker is available at https://github.com/kojiari/smaglinker.

A new oomycete metabarcoding method using the rps10 gene

Oomycetes are a group of eukaryotes related to brown algae and diatoms, many of which cause diseases in plants and animals. Improved methods are needed for rapid and accurate characterization of oomycete communities using DNA metabarcoding. We have identified the mitochondrial 40S ribosomal protein S10 gene (rps10) as a locus useful for oomycete metabarcoding and provide primers predicted to amplify all oomycetes based on available reference sequences from a wide range of taxa. We evaluated its utility relative to a popular barcode, the internal transcribed spacer 1 (ITS1), by sequencing environmental samples and a mock community using Illumina MiSeq. Amplified sequence variants (ASVs) and operational taxonomic units (OTUs) were identified per community. Both the sequence and predicted taxonomy of ASVs and OTUs were compared to the known composition of the mock community. Both rps10 and ITS yielded ASVs with sequences matching 21 of the 24 species in the mock community and matching all 24 when allowing for a 1 bp difference. Taxonomic classifications of ASVs included 23 members of the mock community for rps10 and 17 for ITS1. Sequencing results for the environmental samples suggest the proposed rps10 locus results in substantially less amplification of non-target organisms than the ITS1 method. The amplified rps10 region also has higher taxonomic resolution than ITS1, allowing for greater discrimination of closely related species. We present a new website with a searchable rps10 reference database for species identification and all protocols needed for oomycete metabarcoding. The rps10 barcode and methods described herein provide an effective tool for metabarcoding oomycetes using short-read sequencing.

Simple mapping-based quantification of a mock microbial community using total RNA-seq data

Most microbes in the natural environment are difficult to cultivate. Thus, culture-independent analysis for microbial community structure is important for the understanding of its ecological functions. An immense ribosomal RNA sequence collection is available from phylogenetic research on organisms in all domains. These sequences are available for use in genetic research. However, the amplicon-seq process using PCR requires the construction of a sequence library. Construction can introduce bias into quantitative analyses, and each domain of species needs its own primer set. Total RNA sequencing has the advantage of analyzing an entire microbial community, including bacteria, archea, and eukaryote, at once. Such analysis yields large amounts of ribosomal RNA sequences that can be used for analysis without PCR bias. Evaluation using total RNA-seq for quantitative analysis of microbial communities and comparison with amplicon-seq is still rare. In the present study, we developed a mapping-based total RNA-seq analysis to obtain quantitative information on microbial community structure and compared our results with ordinary amplicon-seq methods. We read total RNA sequences from a commercially available mock community (ATCC MSA-2003) and divided reads into small subunit ribosomal RNA (ssrRNA) origin reads and others, such as mRNA origin reads. We then mapped ssrRNA origin reads on annotated assembled contigs and obtained quantitative results under several analysis strategies. Removal of low complexity sequences, sorting ssrRNA with paired-in mode, and performing homology-based taxonomical assignments (BLAST+ or vsearch) showed superior outcomes to other strategies. Results with this approach showed a median relative abundance among ten mock community members of ~10%; ordinary amplicon-seq showed a much lower percentage. Thus, total RNA-seq can be a powerful tool for analyzing microbial community structure and is not limited to analyzing gene expression profiling of microbiomes.

Comparison of Preservation and Extraction Methods on Five Taxonomically Disparate Coral Microbiomes

All animals are host to a multitude of microorganisms that are essential to the animal’s health. Host-associated microbes have been shown to defend against potential pathogens, provide essential nutrients, interact with the host’s immune system, and even regulate mood. However, it can be difficult to preserve and obtain nucleic acids from some host-associated microbiomes, making studying their microbial communities challenging. Corals are an example of this, in part due to their potentially remote, underwater locations, their thick surface mucopolysaccharide layer, and various inherent molecular inhibitors. This study examined three different preservatives (RNAlater, DNA/RNA Shield, and liquid nitrogen) and two extraction methods (the Qiagen PowerBiofilm kit and the Promega Maxwell RBC kit with modifications) to determine if there was an optimum combination for examining the coral microbiome. These methods were employed across taxonomically diverse coral species, including deep-sea/shallow, stony/soft, and zooxanthellate/azooxanthellate: Lophelia pertusa, Paragorgia johnsoni, Montastraea cavernosa, Porites astreoides, and Stephanocoenia intersepta. Although significant differences were found between preservative types and extraction methods, these differences were subtle, and varied in nature from coral species to coral species. Significant differences between coral species were far more profound than those detected between preservative or extraction method. We suggest that the preservative types presented here and extraction methods using a bead-beating step provide enough consistency to compare coral microbiomes across various studies, as long as subtle differences in microbial communities are attributed to dissimilar methodologies. Additionally, the inclusion of internal controls such as a mock community and extraction blanks can help provide context regarding data quality, improving downstream analyses.

Pre-digest of unprotected DNA by Benzonase improves the representation of living skin bacteria and efficiently depletes host DNA

Background The identification of microbiota based on next-generation sequencing (NGS) of extracted DNA has drastically improved our understanding of the role of microbial communities in health and disease. However, DNA-based microbiome analysis cannot per se differentiate between living and dead microorganisms. In environments such as the skin, host defense mechanisms including antimicrobial peptides and low cutaneous pH result in a high microbial turnover, likely resulting in high numbers of dead cells present and releasing substantial amounts of microbial DNA. NGS analyses may thus lead to inaccurate estimations of microbiome structures and consequently functional capacities. Results We investigated in this study the feasibility of a Benzonase-based approach (BDA) to pre-digest unprotected DNA, i.e., of dead microbial cells, as a method to overcome these limitations, thus offering a more accurate assessment of the living microbiome. A skin mock community as well as skin microbiome samples were analyzed using 16S rRNA gene sequencing and metagenomics sequencing after DNA extraction with and without a Benzonase digest to assess bacterial diversity patterns. The BDA method resulted in less reads from dead bacteria both in the skin mock community and skin swabs spiked with either heat-inactivated bacteria or bacterial-free DNA. This approach also efficiently depleted host DNA reads in samples with high human-to-microbial DNA ratios, with no obvious impact on the microbiome profile. We further observed that low biomass samples generate an α-diversity bias when the bacterial load is lower than 105 CFU and that Benzonase digest is not sufficient to overcome this bias. Conclusions The BDA approach enables both a better assessment of the living microbiota and depletion of host DNA reads. Graphical abstract

Comprehensive benchmarking of tools to identify phages in metagenomic shotgun sequencing data

BackgroundAs the relevance of bacteriophages in shaping diversity in microbial ecosystems is becoming increasingly clear, the prediction of phage sequences in metagenomic datasets has become a topic of considerable interest, which has led to the development of many novel bioinformatic tools. A comprehensive comparative analysis of these tools has so far not been performed.MethodsWe benchmarked ten state-of-the-art phage identification tools. We used artificial contigs generated from complete RefSeq genomes representing phages, plasmids, and chromosomes, and a previously sequenced mock community containing four phage strains to evaluate the precision, recall and F1-scores of the tools. In addition, a set of previously simulated viromes was used to assess diversity bias in each tool’s output.ResultsDeepVirFinder performed best across the datasets of artificial contigs and the mock community, with the highest F1-scores (0.98 and 0.61 respectively). Generally, machine learning-based tools performed better on the artificial contigs, while reference and machine learning based tool performed comparably on the mock community. Most tools produced a viral genome set that had similar alpha and beta diversity patterns to the original population with the notable exception of Seeker, whose metrics differed significantly from the diversity of the underlying data.ConclusionsThis study provides key metrics used to assess performance of phage detection tools, offers a framework for further comparison of additional viral discovery tools, and discusses optimal strategies for using these tools.

A total of 219 metagenome-assembled genomes of microorganisms from Icelandic marine waters

Marine microorganisms contribute to the health of the global ocean by supporting the marine food web and regulating biogeochemical cycles. Assessing marine microbial diversity is a crucial step towards understanding the global ocean. The waters surrounding Iceland are a complex environment where relatively warm salty waters from the Atlantic cool down and sink down to the deep. Microbial studies in this area have focused on photosynthetic micro- and nanoplankton mainly using microscopy and chlorophyll measurements. However, the diversity and function of the bacterial and archaeal picoplankton remains unknown. Here, we used a co-assembly approach supported by a marine mock community to reconstruct metagenome-assembled genomes (MAGs) from 31 metagenomes from the sea surface and seafloor of four oceanographic sampling stations sampled between 2015 and 2018. The resulting 219 MAGs include 191 bacterial, 26 archaeal and two eukaryotic MAGs to bridge the gap in our current knowledge of the global marine microbiome.

Rapid and real-time identification of fungi up to species level with long amplicon Nanopore sequencing from clinical samples

The availability of long-read technologies, like Oxford Nanopore Technologies, provides the opportunity to sequence longer fragments of the fungal ribosomal operon, up to 6 Kb (18S-ITS1-5.8S-ITS2-28S), and to improve the taxonomy assignment of the communities up to species level and in real-time. We assess the applicability for taxonomic assignment of amplicons targeting a 3.5 Kb region (V3 18S-ITS1-5.8S-ITS2-28S D2) and a 6 Kb region (V1 18S-ITS1-5.8S-ITS2-28S D12) with the What's in my pot (WIMP) classifier. We used the ZymoBIOMICSTM mock community and different microbiological fungal cultures as positive controls. Long amplicon sequencing correctly identified Saccharomyces cerevisiae and Cryptococcus neoformans from the mock community and Malassezia pachydermatis, Microsporum canis, and Aspergillus fumigatus from the microbiological cultures. Besides, we identified Rhodotorula graminis in a culture mislabeled as Candida spp. We applied the same approach to external otitis in dogs. Malassezia was the dominant fungal genus in dogs' ear skin, whereas M. pachydermatis was the main species in the healthy sample. Conversely, we identified a higher representation of M. globosa and M. sympodialis in otitis affected samples. We demonstrate the suitability of long ribosomal amplicons to characterize the fungal community of complex samples, either healthy or with clinical signs of infection.

Evaluation of methods for the reduction of contaminating host reads when performing shotgun metagenomic sequencing of the milk microbiome

Shotgun metagenomic sequencing is a valuable tool for the taxonomic and functional profiling of microbial communities. However, this approach is challenging in samples, such as milk, where a low microbial abundance, combined with high levels of host DNA, result in inefficient and uneconomical sequencing. Here we evaluate approaches to deplete host DNA or enrich microbial DNA prior to sequencing using three commercially available kits. We compared the percentage of microbial reads obtained from each kit after shotgun metagenomic sequencing. Using bovine and human milk samples, we determined that host depletion with the MolYsis complete5 kit significantly improved microbial sequencing depth compared to other approaches tested. Importantly, no biases were introduced. Additionally, the increased microbial sequencing depth allowed for further characterization of the microbiome through the generation of metagenome-assembled genomes (MAGs). Furthermore, with the use of a mock community, we compared three common classifiers and determined that Kraken2 was the optimal classifier for these samples. This evaluation shows that microbiome analysis can be performed on both bovine and human milk samples at a much greater resolution without the need for more expensive deep-sequencing approaches.

Metatranscriptomics provides closer diversity and composition estimates with morphology than PCR-based methods: a zooplankton mock community case study

Studying complex metazoan communities requires taxonomic expertise and laborious work if done using the traditional morphological approach. Nowadays, the popular use of molecular-based methods accompanied by massively parallel sequencing (MPS) provides rapid and higher resolution diversity analyses. However, diversity estimates derived from the molecular-based approach can be biased by the co-detection of environmental DNA (eDNA), pseudogene contamination, and PCR amplification biases. Here, we constructed microcrustacean zooplankton mock communities to compare species diversity and composition estimates from PCR-based methods using genomic (gDNA) and complementary DNA (cDNA), metatranscriptomic transcripts, and morphology data. Mock community analyses show that gDNA mitochondrial cytochrome c oxidase I (mtCOI) amplicons inflate species richness due to environmental and nontarget species sequence contamination. Significantly higher amplicon sequence variant (ASV) and nucleotide diversity in gDNA amplicons than cDNA indicated the presence of putative pseudogenes. Last, PCR-based methods failed to detect the most abundant species in mock communities due to priming site mismatch. Overall, metatranscriptomic transcripts provided estimates of species richness and composition that closely resembled morphological data. The use of metatranscriptomic transcripts was further tested in field samples. The results showed that it could provide consistent species diversity estimates among biological and technical replicates while allowing monitoring of the zooplankton temporal species composition changes using different mitochondrial markers. These findings show that community characterization based on metatranscriptomic transcripts reflects the actual community more than PCR-based approaches.