Single-cell genomics is already digging beneath broad averages and uncovering the cellular heterogeneity of tissues. And now, according to a new study from Waseda University and bitBiome researchers, single-cell genomics can do the same for microbiomes.

Bringing single-cell genomics into this new domain is important because metagenomics, the traditional means of examining microbial populations, falls short in resolving microbial diversity at the strain level and in accurately profiling genes involved in antibiotic resistance. These limitations highlight the need for more advanced approaches.

Consequently, the Waseda/bitBiome team has proposed that metagenome-assembled genomes (MAGs) be supplemented by single amplified genomes (SAGs). MAGs, as population consensus genomes, often aggregate heterogeneity among species and strains, obfuscating the relationships between microbial hosts and mobile genetic elements (MGEs). In contrast, SAGs, which are constructed via single-cell genome sequencing, can capture individual genomic content, including MGEs, which may harbor antibiotic resistance genes (ARGs).

The research team, which was led by Masahito Hosokawa, PhD, an associate professor of medical bioscience at Waseda University and the founder and CSO of bioBiome, recently described their work in Microbiome, in a paper titled, “A single amplified genome catalog reveals the dynamics of mobilome and resistome in the human microbiome.”

The paper detailed how the researchers conducted a large-scale individual analysis of microbes in the human body. For this, they recruited 51 participants and collected their saliva and fecal samples. They then performed a new single-cell genome analysis method called SAG-gel technology, commercialized as bit-MAP by bitBiome. In this technique, individual bacteria were enclosed in a gel and their genomes were amplified and analyzed individually.

“We present the bbsag20 dataset, which comprises 17,202 SAGs of medium-quality and above derived from the human oral and gut microbiomes of Japanese individuals using SAG-gel technology,” the article’s authors reported. “This dataset, being one of the largest human oral and gut bacterial SAGs, offers a rich resource for exploring the intricate dynamics of the microbiomes, mobilomes, and resistomes.

“We uncovered compelling evidence of oral bacterial translocation to the gut at the cellular level. Furthermore, we elucidated unexpectedly broad host ranges of plasmids and phages and detailed individual differences in ARG and MGE prevalence and their networks.”

The researchers concluded that combining SAGs and MAGs would be effective in expanding the genome catalog. Also, by connecting mobilomes and resistomes in individual samples, SAGs could be used to chart a dynamic network of ARGs on MGEs, pinpointing potential ARG reservoirs and their spreading patterns in the microbial community.

“The limitation of metagenomics inspired us to develop a new approach to explore the human microbiome at the single-cell level,” said Hosokawa. “This single-cell genome approach can enhance our understanding of how bacteria interact and exchange genetic material including antibiotic resistance genes, providing deeper insights into human health and disease.”

The researchers recovered genomes of 300 bacterial species using this novel technique which were missed by the conventional method. In addition, the new technique provided deeper insights into antibiotic resistance genes, gene exchange networks, bacterial interaction, and diversity.

“Our study analyzed 30,000 individual genomes of oral and intestinal bacteria, which is the world’s largest genome dataset, showcasing the power of single-cell genomics in elucidating microbial diversity and interactions,” Hosokawa noted.

The findings of this study have several potential applications. In public health, the detailed profiling of antibiotic resistance genes can help develop more targeted and effective treatment strategies. This in turn can help prevent diseases, reduce healthcare costs, and improve public health. In environmental monitoring, single-cell genomics can track genetic shifts across ecosystems to manage and prevent the spread of antibiotic resistance. In the agricultural sector, understanding antibiotic resistance gene dynamics can guide practices to minimize resistance spread through soil, water, and livestock.

The study highlights the transformative potential of single-cell genomics in microbiome research, and it suggests how a more detailed and nuanced understanding of microbial communities could be gained. “Our approach,” Hosokawa concluded, “provides clues to better understand how antibiotic resistance spreads in bacteria and has potential for future medical and public health applications.”

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