Metagenomic analysis has greatly advanced our understanding of the human microbiome. However, metagenome-assembled genomes are often imprecise and are unable to sufficiently differentiate between closely related species. Now, researchers from Waseda University have developed a novel integrated framework that combines single-cell genomics and metagenomics to yield better genome recovery and accurate resolution of microbial populations in the human microbiome.
The human microbiome
The microbial inhabitants of the human body (the human microbiome) play an integral role in maintaining the overall health of the body. These microbes usually exist in harmony, maintaining normal physiological processes. However, an imbalance in their abundance can trigger various chronic diseases ranging from gastrointestinal inflammatory and metabolic conditions to neurological, cardiovascular and respiratory illnesses. Therefore, considerable efforts are being made to characterise the various microbes that constitute the human microbiome to try and understand the role of host-microbiome relationships in health and disease.
Single-cell and metagenomics for the human microbiome
Metagenomics is an advanced DNA sequencing technique that enables direct extraction and in silico characterisation of genetic material from mixed microbial populations. This method is favoured as it bypasses the time-consuming task of isolating and culturing different bacterial species from the mixture. However, while this technique is useful for obtaining a broader picture of the human microbiome, finer details across closely related species can be missed, thereby contributing to bias and inaccuracy.
Meanwhile, single-cell genomics is a promising alternative approach for culture-independent sequencing of microbial genomes. In contrast to metagenomics, this method does not require microbial population clonality, and instead recovers genome sequences from individual cells. However, in single-cell genomics, DNA amplification often causes amplification biases and incompleteness in genome sequences.
Combining singe-cell and metagenomics
Therefore, to try and overcome the pitfalls of both single-cell genomics and metagenomics when applied to the human genome, this pioneering study, published in Microbiome, tested a hybrid approach combining both techniques.
Lead researcher on the study, Associate Professor Masahito Hosokawa, explained, ‘Bacterial genomes reconstructed from metagenomic analyses alone are imperfect and contain errors. We have developed a novel single cell metagenomics integration framework, termed SMAGLinker, which determines the genome sequence of each cell individually. Using this method, we aim to obtain accurate bacterial genomes comprehensively, which has been a challenge in the past’.
They first generated single-cell amplified genomes (SAG) for the human gut and skin microbiota. They also generated a SAG for a mock microbial community containing known bacteria for validation. The team then analysed and clustered the sequences, using a method known as contig binning. They integrated this analysis with metagenome-assembled genomes (MAG) to improve the overall coverage and accuracy of microbial genomes.
Comparing combined single-cell and metagenomic approaches with conventional metagenomics
When comparing their integrated approach – SMAGLinker – with conventional metagenomics, they found that their method showed higher accuracy and precise categorisation (>97%). Most notably, SMAGLinker demonstrated a higher genome recovery rate, compared to the conventional approach.
Using SMAGLinker, the researchers were able to construct a large number of high-quality genomes from the gut and skin microbiota. Moreover, genomes obtained using this approach spanned a larger number of bacterial genera, indicating better coverage of bacterial diversity.
The researchers were also able to obtain better resolution of intraspecies diversity using SMAGLinker. More specifically, the conventional metagenomic approach only revealed one genome of the bacterium Staphylococcus hominis, contaminated with other Staphylococcus species genomes. Meanwhile, SMAGLinker was able to identify two independent strains harbouring distinct plasmids from the same skin microbiota sample. The researchers were also able to validate their findings using the mock microbial sample.
Summary and future implications
In summary, SMAGLinker is a powerful tool that can improve the accuracy and quality of genome recovery and resolution of closely related microbial genomes in the human microbiome.
When asked about the potential ramifications of their study, Hosokawa concludes, ‘Human commensal bacteria are deeply related to human health and understanding host-microbe interactions is important for designing novel medical treatments as well as for industrial and environmental applications. We are hopeful that this technology can be extended across diverse research disciplines for accurate microbial characterization’.
Image credit: Olique – canva
