Transforming Microbiome Research with Single-Cell Genome Analysis

The human microbiome plays a critical role in our health, influencing everything from disease development to treatment responses. This connection has captured the attention of scientists worldwide, eager to unlock its secrets. While traditional metagenomics has provided valuable insights, it falls short in resolving microbial diversity at the strain level and accurately profiling genes involved in antibiotic resistance. These limitations highlight the need for more advanced approaches.

To address this, a team of researchers led by Associate Professor Masahito Hosokawa, from Waseda University, in collaboration with bitBiome, Inc., developed a groundbreaking single-cell genome approach. This approach, which reads information from individual cells, offers a promising alternative to conventional metagenomics. This study, published in Microbiome on 02 October 2024, explores the microbial diversity and genetic features using single-cell genomic analysis.

"The limitation of metagenomics inspired us to develop a new approach to explore the human microbiome at the single-cell level. 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," says Hosokawa.

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, Inc. In this technique, individual bacteria were enclosed in a gel and their genomes were amplified and analyzed individually.

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," says Hosokawa.

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, offering a more detailed and nuanced understanding of microbial communities.

"Our approach provides clues to better understand how antibiotic resistance spreads in bacteria and has potential for future medical and public health applications," concludes Hosokawa.

Source:
Journal reference:

Kawano-Sugaya, T., et al. (2024). A single amplified genome catalog reveals the dynamics of mobilome and resistome in the human microbiome. Microbiome. doi.org/10.1186/s40168-024-01903-z.

Comments

The opinions expressed here are the views of the writer and do not necessarily reflect the views and opinions of AZoLifeSciences.
Post a new comment
Post

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.

You might also like...
New Lab-Grown Lip Cells Could Transform Research and Treatment for Disfiguring Lip Conditions