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Abstract Background The increase in metagenome-assembled genomes (MAGs) has advanced our understanding of the functional characterization and taxonomic assignment within the human microbiome. However, MAGs, as population consensus genomes, often aggregate heterogeneity among species and strains, thereby obfuscating the precise relationships between microbial hosts and mobile genetic elements (MGEs). In contrast, single amplified genomes (SAGs) derived via single-cell genome sequencing can capture individual genomic content, including MGEs. Results We introduce the first substantial SAG dataset (bbsag20) from the human oral and gut microbiome, comprising 17,202 SAGs above medium-quality without co-assembly. This collection unveils a diversity of bacterial lineages across 312 oral and 647 gut species, demonstrating different taxonomic compositions from MAGs. Moreover, the SAGs showed cellular-level evidence of the translocation of oral bacteria to the gut. We also identified broad-host-range MGEs harboring antibiotic resistance genes (ARGs), which were not detected in the MAGs. Conclusions The difference in taxonomic composition between SAGs and MAGs indicates that combining both methods would be effective in expanding the genome catalog. By connecting mobilomes and resistomes in individual samples, SAGs could meticulously chart a dynamic network of ARGs on MGEs, pinpointing potential ARG reservoirs and their spreading patterns in the microbial community. Video Abstract

Abstract Culture-independent analysis with high-throughput sequencing has been widely used to characterize bacterial communities. However, signals derived from non-viable bacteria and non-cell DNA may inhibit its characterization. Here, we present a method for viable bacteria-targeted single-cell genome sequencing, called PMA-SAG-gel, to obtain comprehensive whole-genome sequences of surviving uncultured bacteria from microbial communities. PMA-SAG-gel uses gel matrixes that enable sequential enzymatic reactions for cell lysis and genome amplification of viable single cells from the microbial communities. PMA-SAG-gel removed the single-amplified genomes (SAGs) derived from dead bacteria and enabled selective sequencing of viable bacteria in the model samples of Escherichia coli and Bacillus subtilis. Next, we demonstrated the recovery of near-complete SAGs of eight oxygen-tolerant bacteria, including Bacteroides spp. and Phocaeicola spp., from 1331 human feces SAGs. We found the presence of two different strains in each species and identified their specific genes to investigate the metabolic functions. The survival profile of an entire population at the strain level will provide the information for understanding the characteristics of the surviving bacteria under the specific environments or sample processing and insights for quality assessment of live bacterial products or fecal microbiota transplantation and for understanding the effect of antimicrobial treatments.

Obtaining complete and accurate bacterial genomes is vital for studying the characteristics of uncultured bacteria. Single-cell genomics is a promising approach for the culture-independent recovery of bacterial genomes from individual cells. However, single-amplified genomes (SAGs) often have fragmented and incomplete sequences due to chimeric and biased sequences introduced during the genome amplification process. To address this, we developed a single-cell amplified genome long-read assembly (scALA) workflow to construct complete circular SAGs (cSAGs) from long-read single-cell sequencing data of uncultured bacteria. We used the SAG-gel platform, which is both cost-effective and high-throughput, to obtain hundreds of short-read and long-read sequencing data for specific bacterial strains. The scALA workflow generated cSAGs by repeated in silico processing for sequence bias reduction and contig assembly. From 12 human fecal samples, including two cohabitant groups, scALA generated 16 cSAGs of three specifically targeted bacterial species: Anaerostipes hadrus, Agathobacter rectalis, and Ruminococcus gnavus. We discovered strain-specific structural variations shared among cohabiting hosts, while all cSAGs of the same species showed high homology in aligned genomic regions. A. hadrus cSAGs exhibited 10 kbp-long phage insertions, various saccharide metabolic capabilities, and different CRISPR-Cas systems in each strain. The sequence similarity of A. hadrus genomes did not necessarily correspond with orthologous functional genes, while host geographical regionality seemed to be highly related to gene possession. scALA allowed us to obtain closed circular genomes of specifically targeted bacteria from human microbiota samples, leading to an understanding of within-species diversities, including structural variations and linking mobile genetic elements, such as phages, to hosts. These analyses provide insight into microbial evolution, the adaptation of the community to environmental changes, and interactions with hosts. cSAGs constructed using this method can expand bacterial genome databases and our understanding of within-species diversities in uncultured bacteria.

Abstract 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 . Video abstract

To understand the role of the skin commensal bacterial community in skin health and the spread of pathogens, it is crucial to identify genetic differences in the bacterial strains corresponding to human individuals. A culture-independent genomics approach is an effective tool for obtaining massive high-quality bacterial genomes. Here we present a single-cell genome sequencing to obtain comprehensive whole-genome sequences of uncultured skin bacteria from skin swabs. We recovered 281 high-quality (HQ) and 244 medium-quality single-amplified genomes (SAGs) of multiple skin bacterial species from eight individuals, including cohabiting group. Single-cell sequencing outperformed in the genome recovery from the same skin swabs, showing 10-fold non-redundant strain genomes compared to the shotgun metagenomic sequencing and binning approach. We then focused on the abundant skin bacteria and identified intra-species diversity, especially in 47 Moraxella osloensis derived HQ SAGs, characterizing the strain-level heterogeneity at mobile genetic element profiles, including plasmids and prophages. Even between the cohabiting individual hosts, they have unique skin bacterial strains in the same species, which shows microdiversity in each host. Genetic and functional differences between skin bacterial strains are predictive of in vivo competition to adapt bacterial genome to utilize the sparse nutrients available on the skin or produce molecules that inhibit the colonization of other microbes or alter their behavior. Thus, single-cell sequencing provides a large number of genomes of higher resolution and quality than conventional metagenomic analysis and helps explore the skin commensal bacteria at the strain level, linking taxonomic and functional information.

Detection and identification of microbial species are crucial in a wide range of industries, including production of beverages, foods, cosmetics, and pharmaceuticals. Traditionally, colony formation and its morphological analysis (e.g., size, shape, and color) with a naked eye have been employed for this purpose. However, such a conventional method is time consuming, labor intensive, and not very reproducible. To overcome these problems, we propose a novel method that detects microcolonies (diameter 10-500 μm) using a lensless imaging system. When comparing colony images of five microorganisms from different genera (Escherichia coli, Salmonella enterica, Pseudomonas aeruginosa, Staphylococcus aureus, and Candida albicans), the images showed obvious different features. Being closely related species, St. aureus and St. epidermidis resembled each other, but the imaging analysis could extract substantial information (colony fingerprints) including the morphological and physiological features, and linear discriminant analysis of the colony fingerprints distinguished these two species with 100% of accuracy. Because this system may offer many advantages such as high-throughput testing, lower costs, more compact equipment, and ease of automation, it holds promise for microbial detection and identification in various academic and industrial areas.

Experimental and theoretical studies were conducted on the separation of submicron powder using a revised type of cyclone. The cyclone has a movable inlet guide plate at the inlet section, and 50% cut size is controlled from 0.45 to 0.75 μm by changing the inlet clearance of the guide plate. But the 50% cut size increases again with a very narrow inlet clearance of the guide plate, because the radial velocity of particles decreases and fluid turbulence increases under such condition. The 50% cut size decreases to about 0.4 μm when both the inlet guide plate and the blowdown method are used. The partial separation efficiency with a spiral-inlet cyclone is higher than a cyclone with tangential inlet, and the 50% cut size decreases with a highly polished inside wall surface. † This report was originally printed in KAGAKU KOGAKU RONBUNSHU, 19(3), 476-482 (1993) in Japanese, before being translated into English by KONA Editorial Committee with the permission of the editorial committee of the Soc. Chemical Engineers, Japan.

In this paper, we present a novel cell counting method accomplished using a single-cell array fabricated on an image sensor, complementary metal oxide semiconductor sensor. The single-cell array was constructed using a microcavity array, which can trap up to 7,500 single cells on microcavities periodically arranged on a plane metallic substrate via the application of a negative pressure. The proposed method for cell counting is based on shadow imaging, which uses a light diffraction pattern generated by the microcavity array and trapped cells. Under illumination, the cell-occupied microcavities are visualized as shadow patterns in an image recorded by the complementary metal oxide semiconductor sensor due to light attenuation. The cell count is determined by enumerating the uniform shadow patterns created from one-on-one relationships with single cells trapped on the microcavities in digital format. In the experiment, all cell counting processes including entrapment of non-labeled HeLa cells from suspensions on the array and image acquisition of a wide-field-of-view of 30 mm(2) in 1/60 seconds were implemented in a single integrated device. As a result, the results from the digital cell counting had a linear relationship with those obtained from microscopic observation (r(2) = 0.99). This platform could be used at extremely low cell concentrations, i.e., 25-15,000 cells/mL. Our proposed system provides a simple and rapid miniaturized cell counting device for routine laboratory use.