Strain-level profiling of viable microbial community by selective single-cell genome sequencing

Single-cell genomics of single soil aggregates: methodological assessment and potential implications with a focus on nitrogen metabolism

Soil particles in plant rooting zones are largely clustered to form porous structural units called aggregates where highly diverse microorganisms inhabit and drive biogeochemical cycling. The complete extraction of microbial cells and DNA from soil is a substantial task as certain microorganisms exhibit strong adhesion to soil surfaces and/or inhabit deep within aggregates. However, the degree of aggregate dispersion and the efficacy of extraction have rarely been examined, and thus, adequate cell extraction methods from soil remain unclear. We aimed to develop an optimal method of cell extraction for single-cell genomics (SCG) analysis of single soil aggregates by focusing on water-stable macroaggregates (diameter: 5.6-8.2 mm) from the topsoil of cultivated Acrisol. We postulated that the extraction of microorganisms with distinct taxonomy and functions could be achieved depending on the degree of soil aggregate dispersion. To test this idea, we used six individual aggregates and performed both SCG sequencing and amplicon analysis. While both bead-vortexing and sonication dispersion techniques improved the extractability of bacterial cells compared to previous ones, the sonication technique led to more efficient dispersion and yielded a higher number and more diverse microorganisms than the bead technique. Furthermore, the analyses of nitrogen cycling and exopolysaccharides-related genes suggested that the sonication-assisted extraction led to the greater recovery of microorganisms strongly attached to soil particles and/or inhabited the aggregate subunits that were more physically stable (e.g., aggregate core). Further SCG analysis revealed that all six aggregates held intact microorganisms holding the genes (potentials) to convert nitrate into all possible nitrogen forms while some low-abundance genes showed inter-aggregate heterogeneity. Overall, all six aggregates studied showed similarities in pore characteristics, phylum-level composition, and microbial functional redundancy. Together, these results suggest that water-stable macroaggregates may act as a functional unit in soil and show potential as a useful experimental unit in soil microbial ecology. Our study also suggests that conventional methods employed for the extraction of cells and DNA may not be optimal. The findings of this study emphasize the necessity of advancing extraction methodologies to facilitate a more comprehensive understanding of microbial diversity and function in soil environments.

High throughput single cell metagenomic sequencing with semi-permeable capsules: unraveling microbial diversity at the single-cell level in sewage and fecal microbiomes

Single-cell sequencing may serve as a powerful complementary technique to shotgun metagenomics to study microbiomes. This emerging technology allows the separation of complex microbial communities into individual bacterial cells, enabling high-throughput sequencing of genetic material from thousands of singular bacterial cells in parallel. Here, we validated the use of microfluidics and semi-permeable capsules (SPCs) technology (Atrandi) to isolate individual bacterial cells from sewage and pig fecal samples. Our method involves extracting and amplifying single bacterial DNA within individual SPCs, followed by combinatorial split-and-pool single-amplified genome (SAG) barcoding and short-read sequencing. We tested two different sequencing approaches with different numbers of SPCs from the same sample for each sequencing run. Using a deep sequencing approach, we detected 1,796 and 1,220 SAGs, of which 576 and 599 were used for further analysis from one sewage and one fecal sample, respectively. In shallow sequencing data, we aimed for 10-times more cells and detected 12,731 and 17,909 SAGs, of which we used 2,456 and 1,599 for further analysis for sewage and fecal samples, respectively. Additionally, we identified the top 10 antimicrobial resistance genes (ARGs) in both sewage and feces samples and linked them to their individual host bacterial species.

Advancements in the Impact of Insect Gut Microbiota on Host Feeding Behaviors

With the application and development of high-throughput sequencing technology, the structure and function of insect gut microbiota have been analysed, which lays a foundation for further exploring the intricate relationships between gut microbiota and host feeding behaviour. The microbial community in the insect gut, as an important ecological factor, affects the host's food selection and nutritional metabolic processes through various mechanisms, which play a key role in population dynamics and ecosystems. The implications of these interactions are profound, affecting agricultural practices, biodiversity, and the broader environment, such as pollination and pest control. In-depth exploration of the molecular mechanism of the interaction between gut microbiota and hosts contributes to the grasp of insect biology and evolution and offers novel avenues for manipulating insect behaviour for practical applications in agriculture and environmental management. This paper focuses on the possible mechanisms of insect gut microbiota regulating host feeding behaviour. It inspires further research on the interaction between gut microbiota and insects affecting host behaviour.

A single amplified genome catalog reveals the dynamics of mobilome and resistome in the human microbiome

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.

Uncovering Endolysins against Methicillin-Resistant Staphylococcus aureus Using a Microbial Single-Cell Genome Database

Endolysins, peptidoglycan hydrolases derived from bacteriophages (phages), are being developed as a promising alternative to conventional antibiotics. To obtain highly active endolysins, a diverse library of these endolysins is vital. We propose here microbial single-cell genome sequencing as an efficient tool to discover dozens of previously unknown endolysins, owing to its culture-independent sequencing method. As a proof of concept, we analyzed and recovered endolysin genes within prophage regions of Staphylococcus single-amplified genomes in human skin microbiome samples. We constructed a library of chimeric endolysins by shuffling domains of the natural endolysins and performed high-throughput screening against Staphylococcus aureus. One of the lead endolysins, bbst1027, exhibited desirable antimicrobial properties, such as rapid bactericidal activity, no detectable resistance development, and in vivo efficacy. We foresee that this endolysin discovery pipeline is in principle applicable to any bacterial target and boost the development of novel antimicrobial agents.

Tools for microbial single-cell genomics for obtaining uncultured microbial genomes

The advent of next-generation sequencing technologies has facilitated the acquisition of large amounts of DNA sequence data at a relatively low cost, leading to numerous breakthroughs in decoding microbial genomes. Among the various genome sequencing activities, metagenomic analysis, which entails the direct analysis of uncultured microbial DNA, has had a profound impact on microbiome research and has emerged as an indispensable technology in this field. Despite its valuable contributions, metagenomic analysis is a "bulk analysis" technique that analyzes samples containing a wide diversity of microbes, such as bacteria, yielding information that is averaged across the entire microbial population. In order to gain a deeper understanding of the heterogeneous nature of the microbial world, there is a growing need for single-cell analysis, similar to its use in human cell biology. With this paradigm shift in mind, comprehensive single-cell genomics technology has become a much-anticipated innovation that is now poised to revolutionize microbiome research. It has the potential to enable the discovery of differences at the strain level and to facilitate a more comprehensive examination of microbial ecosystems. In this review, we summarize the current state-of-the-art in microbial single-cell genomics, highlighting the potential impact of this technology on our understanding of the microbial world. The successful implementation of this technology is expected to have a profound impact in the field, leading to new discoveries and insights into the diversity and evolution of microbes.

Microbial evolution through horizontal gene transfer by mobile genetic elements

Mobile genetic elements (MGEs) are crucial for horizontal gene transfer (HGT) in bacteria and facilitate their rapid evolution and adaptation. MGEs include plasmids, integrative and conjugative elements, transposons, insertion sequences and bacteriophages. Notably, the spread of antimicrobial resistance genes (ARGs), which poses a serious threat to public health, is primarily attributable to HGT through MGEs. This mini-review aims to provide an overview of the mechanisms by which MGEs mediate HGT in microbes. Specifically, the behaviour of conjugative plasmids in different environments and conditions was discussed, and recent methodologies for tracing the dynamics of MGEs were summarised. A comprehensive understanding of the mechanisms underlying HGT and the role of MGEs in bacterial evolution and adaptation is important to develop strategies to combat the spread of ARGs.

Single-cell analysis and spatial resolution of the gut microbiome

Over the past decade it has become clear that various aspects of host physiology, metabolism, and immunity are intimately associated with the microbiome and its interactions with the host. Specifically, the gut microbiome composition and function has been shown to play a critical role in the etiology of different intestinal and extra-intestinal diseases. While attempts to identify a common pattern of microbial dysbiosis linked with these diseases have failed, multiple studies show that bacterial communities in the gut are spatially organized and that disrupted spatial organization of the gut microbiome is often a common underlying feature of disease pathogenesis. As a result, focus over the last few years has shifted from analyzing the diversity of gut microbiome by sequencing of the entire microbial community, towards understanding the gut microbiome in spatial context. Defining the composition and spatial heterogeneity of the microbiome is critical to facilitate further understanding of the gut microbiome ecology. Development in single cell genomics approach has advanced our understanding of microbial community structure, however, limitations in approaches exist. Single cell genomics is a very powerful and rapidly growing field, primarily used to identify the genetic composition of microbes. A major challenge is to isolate single cells for genomic analyses. This review summarizes the different approaches to study microbial genomes at single-cell resolution. We will review new techniques for microbial single cell sequencing and summarize how these techniques can be applied broadly to answer many questions related to the microbiome composition and spatial heterogeneity. These methods can be used to fill the gaps in our understanding of microbial communities.

Uncultured prokaryotic genomes in the spotlight: An examination of publicly available data from metagenomics and single-cell genomics

Owing to the ineffectiveness of traditional culture techniques for the vast majority of microbial species, culture-independent analyses utilizing next-generation sequencing and bioinformatics have become essential for gaining insight into microbial ecology and function. This mini-review focuses on two essential methods for obtaining genetic information from uncultured prokaryotes, metagenomics and single-cell genomics. We analyzed the registration status of uncultured prokaryotic genome data from major public databases and assessed the advantages and limitations of both the methods. Metagenomics generates a significant quantity of sequence data and multiple prokaryotic genomes using straightforward experimental procedures. However, in ecosystems with high microbial diversity, such as soil, most genes are presented as brief, disconnected contigs, and lack association of highly conserved genes and mobile genetic elements with individual species genomes. Although technically more challenging, single-cell genomics offers valuable insights into complex ecosystems by providing strain-resolved genomes, addressing issues in metagenomics. Recent technological advancements, such as long-read sequencing, machine learning algorithms, and in silico protein structure prediction, in combination with vast genomic data, have the potential to overcome the current technical challenges and facilitate a deeper understanding of uncultured microbial ecosystems and microbial dark matter genes and proteins. In light of this, it is imperative that continued innovation in both methods and technologies take place to create high-quality reference genome databases that will support future microbial research and industrial applications.

Assessing the impact of meta-genomic tools on current cutting-edge genome engineering and technology

Metagenomics is defined as the study of the genome of the total microbiota found in nature and is often referred to as microbial environmental genomics because it entails the examination of a group of genetic components (genomes) from a diverse community of organisms in a particular setting. It is a sub-branch of omics technology that encompasses Deoxyribonucleic Acid (DNA), Ribonucleic acid (DNA), proteins, and various components associated with comprehensive analysis of all aspects of biological molecules in a system-wide manner. Clustered regularly interspaced palindromic repeats and its endonuclease, CRISPR-associated protein which forms a complex called CRISPR-cas9 technology, though it is a different technique used to make precise changes to the genome of an organism, it can be used in conjunction with metagenomic approaches to give a better, rapid, and more accurate description of genomes and sequence reads. There have been ongoing improvements in sequencing that have deepened our understanding of microbial genomes forever. From the time when only a small amount of gene could be sequenced using traditional methods (e.g., "the plus and minus" method developed by Allan and Sanger and the "chemical cleavage" method that is known for its use in the sequencing the phiX174 bacteriophage genome via radio-labeled DNA polymerase-primer in a polymerization reaction aided by polyacrylamide gel) to the era of total genomes sequencing which includes "sequencing-by-ligation" and the "sequencing-by-synthesis" that detects hydrogen ions when new DNA is synthesized (Second Generation) and then Next Generation Sequencing technologies (NGS). With these technologies, the Human Genome Project (HGP) was made possible. The study looks at recent advancements in metagenomics in plants and animals by examining findings from randomly selected research papers. All selected case studies examined the functional and taxonomical analysis of different microbial communities using high-throughput sequencing to generate different sequence reads. In animals, five studies indicated how Zebrafish, Livestock, Poultry, cattle, niches, and the human microbiome were exploited using environmental samples, such as soil and water, to identify microbial communities and their functions. It has also been used to study the microbiome of humans and other organisms, including gut microbiomes. Recent studies demonstrated how these technologies have allowed for faster and more accurate identification of pathogens, leading to improved disease diagnostics. They have also enabled the development of personalized medicine by allowing for the identification of genetic variations that can impact drug efficacy and toxicity. Continued advancements in sequencing techniques and the refinement of CRISPR-Cas9 tools offer even greater potential for transformative breakthroughs in scientific research and applications. On the other hand, metagenomic data are always large and uneasy to handle. The complexity of taxonomical profiling, functional annotation, and mechanisms of complex interaction still needs better bioinformatics tools. Current review focuses on better (e.g., AI-driven algorithms) tools that can predict metabolic pathways and interactions, and manipulate complex data to address potential bias for accurate interpretation.

Target enrichment of uncultured human oral bacteria with phage-derived molecules found by single-cell genomics

Advances in culture-independent microbial analysis, such as metagenomics and single-cell genomics, have significantly increased our understanding of microbial lineages. While these methods have uncovered a large number of novel microbial taxa, many remain uncultured, and their function and mode of existence in the environment are still unknown. This study aims to explore the use of bacteriophage-derived molecules as probes for detecting and isolating uncultured bacteria. Here, we proposed multiplex single-cell sequencing to obtain massive uncultured oral bacterial genomes and searched prophage sequences from over 450 obtained human oral bacterial single-amplified genomes (SAGs). The focus was on the cell wall binding domain (CBD) in phage endolysin, and fluorescent protein-fused CBDs were generated based on several CBD gene sequences predicted from Streptococcus SAGs. The ability of the Streptococcus prophage-derived CBDs to detect and enrich specific Streptococcus species from human saliva while maintaining cell viability was confirmed by magnetic separation and flow cytometry. The approach to phage-derived molecule generation based on uncultured bacterial SAG is expected to improve the process of designing molecules that selectively capture or detect specific bacteria, notably from uncultured gram-positive bacteria, and will have applications in isolation and in situ detection of beneficial or pathogenic bacteria.

Revealing within-species diversity in uncultured human gut bacteria with single-cell long-read sequencing

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.

Massively parallel single-cell genomics of microbiomes in rice paddies

Plant growth-promoting microbes (PGPMs) have attracted increasing attention because they may be useful in increasing crop yield in a low-input and sustainable manner to ensure food security. Previous studies have attempted to understand the principles underlying the rhizosphere ecology and interactions between plants and PGPMs using ribosomal RNA sequencing, metagenomic sequencing, and genome-resolved metagenomics; however, these approaches do not provide comprehensive genomic information for individual species and do not facilitate detailed analyses of plant-microbe interactions. In the present study, we developed a pipeline to analyze the genomic diversity of the rice rhizosphere microbiome at single-cell resolution. We isolated microbial cells from paddy soil and determined their genomic sequences by using massively parallel whole-genome amplification in microfluidic-generated gel capsules. We successfully obtained 3,237 single-amplified genomes in a single experiment, and these genomic sequences provided insights into microbial functions in the paddy ecosystem. Our approach offers a promising platform for gaining novel insights into the roles of microbes in the rice rhizomicrobiome and to develop microbial technologies for improved and sustainable rice production.

Exploring strain diversity of dominant human skin bacterial species using single-cell genome sequencing

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.