Single-cell genomics enabled the exploration of cellular diversity in a broad range of biological samples 1, 2 . Nowadays, the use of this technique allows us to identify the genomes of uncultivable microorganism 3, 4 , genetic mosaicism in tissues 5 , and intra-tumor heterogeneity 6 , which brings new perspectives to our understanding by revealing the role of individual cells in the biology of complex ecosystems and organisms. However, we still face several technical challenges in the sample preparation process, including effective isolation and lysis of single cells, uniform amplification of whole genome, quality assessment of single-cell amplified genomes (SAGs), sequencing library preparation, and sequencing analysis. Among all, to maximize the quality and throughput of single-cell sequencing, there is a great demand for novel techniques, which enable massively parallel whole genome amplification (WGA) with high accuracy.Microfluidic-based WGA represents one approach to achieve high-throughput and high fidelity single cell genomics. Microfluidic devices, including in-house 7-9 and commercially available valve-controlled microfluidic circuit (Fluidigm C1) 10, 11 and microwell 12, 13 , can integrate labor-intensive experimental WGA processes in a single, closed device and minimize the running cost and the risk of contamination that frequently occurs in bench-top experimentation. The reaction in microfluidic environment offers advantages over tube-based approaches, including improved reaction efficiency and detection sensitivity at the single-molecule level. In particular, droplet microfluidics has garnered the attention due to its scalability for various single cell studies 14 . Recently, we and other groups also developed the compartmented droplet multiple displacement amplification (cd-MDA) technique for bias-less single-cell WGA [15][16][17][18] . By distributing and amplifying single-cell genome

Background: The gut microbiota can have dramatic effects on host metabolism; however, current genomic strategies for uncultured bacteria have several limitations that hinder their ability to identify responders to metabolic changes in the microbiota. In this study, we describe a novel single-cell genomic sequencing technique that can identify metabolic responders at the species level without the need for reference genomes, and apply this method to identify bacterial responders to an inulin-based diet in the mouse gut microbiota. Results: Inulin-feeding changed the mouse fecal microbiome composition to increase Bacteroides spp., resulting in the production of abundant succinate in the mouse intestine. Using our massively parallel single-cell genome sequencing technique, named SAG-gel platform, we obtained 346 single-amplified genomes (SAGs) from mouse gut microbes before and after dietary inulin supplementation. After quality control, the SAGs were classified as 267 bacteria, spanning 2 phyla, 4 classes, 7 orders, and 14 families, and 31 different strains of SAGs were graded as highand medium-quality draft genomes. From these, we have successfully obtained the genomes of the dominant inulin-responders, Bacteroides spp., and identified their polysaccharide utilization loci and their specific metabolic pathways for succinate production. Conclusions: Our single-cell genomics approach generated a massive amount of SAGs, enabling a functional analysis of uncultured bacteria in the intestinal microbiome. This enabled us to estimate metabolic lineages involved in the bacterial fermentation of dietary fiber and metabolic outcomes such as short-chain fatty acid production in the intestinal environment based on the fibers ingested. The technique allows the in-depth isolation and characterization of uncultured bacteria with specific functions in the microbiota and could be exploited to improve human and animal health.

Single-cell genomics is a straightforward approach to obtain genomes from uncultured microbes. However, sequence reads from a single-cell amplified genome (SAG) contain significant bias and chimeric sequences. Here, we describe Cleaning and Co-assembly of a Single-Cell Amplified Genome (ccSAG), a novel analytical workflow to obtain composite single-cell genomes with elimination of sequence errors. By the integration of ccSAG with a massively parallel single-cell genome amplification platform based on droplet microfluidics, we can generate multiple SAGs and effectively integrate them into the composite genomes quality equivalent to the data obtained from bulk DNA. We obtained two novel draft genomes from single gut microbial cells with high completeness (>96.6%) and extremely low contamination (<1.25%). Moreover, we revealed the presence of single nucleotide polymorphisms in the specific gene by sequence comparison at the single-cell level. Thus, the workflow yields near-complete genomes from uncultured microbes, and enables analyses of genetic heterogeneity within identical strains.

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.

Single-cell genomics is applied to environmental samples as a method to solve the problems of current metagenomics. However, in the fluorescence-activated cell sorting-based cell isolation and subsequent whole genome amplification, the sorting efficiency and the sequence quality are greatly affected by the type of target environment, limiting its adaptability. Here, we developed an improved single-cell genomics platform, named SAG-gel, which utilizes gel beads for single-cell isolation, lysis, and whole genome amplification. To validate the versatility of SAG-gel, single-cell genome sequencing was performed with model bacteria and microbial samples collected from eight environmental sites, including soil and seawater. Gel beads enabled multiple lysis treatments. The genome coverage with model bacteria was improved by 9.1–25%. A total of 734 single amplified genomes were collected from the diverse environmental samples, and almost full-length 16S rRNA genes were recovered from 57.8% of them. We also revealed two marine Rhodobacter strains harboring nearly identical 16S rRNA genes but having different genome contents. In addition, searching for viral sequences elucidated the virus-host linkage over the sampling sites, revealing the geographic distribution and diverse host range of viruses.