Application of Metagenomic Sequencing in Intestinal Microflora Research

The continuous progress of sequencing technology is an important driving force for the development of life sciences, and the rise of the field of microbiomes is even more dependent on the widespread application of metagenomic next-generation sequencing technology.

Analysis of structural variation and function of intestinal microflora by Long-read metagenomic sequencing

The role of intestinal microbiomes in human health and diseases has received increasing attention and has become a hot topic in the field of life science research in the past decade. A recent study characterizes fine-scale genetic variations of structural variations (SVs) in hundreds of gut microbiomes from healthy humans by harnessing the advantage of long-read sequencing provided by Oxford Nanopore Technology (ONT). This study finds that SV is highly diverse among individuals and stable within individuals, representing gut microbiome fingerprints that form functional strain level differences within species, complicating associations with metabolites and host phenotypes such as blood glucose. These results benefit from ONT long reads, which enormously improve the quality of metagenomic combinations and can reliably detect a large number of extended structural variation types. This study demonstrated that incorporating ONT reads into metagenomic analyses expands the detection scope of genetic variations, and enables profiling strain-level variations in gut microbiome, and their intricate correlations with metabolome.

Figure1. ONT reads improved metagenomic assembly, empowered structural variations (SVs) detection and validations.

Long-read sequencing assist in the construction and research of intestinal metagenomes

Intestinal flora plays an important role in horse health, disease, athletic performance, and behavior. Therefore, it is important to have a detailed understanding of the composition and function of horse intestinal flora in order to potentially improve the use of horses in human activities. Researchers employed Illumina sequencing on 110 caecum and 132 rectal (fecal) samples from 242 horses, which were maintained under different dietary conditions, and involved different ages (1-11 years old), different genders (female, male), and different breeds and ultimately obtained 2.264 Tb clean data. From long-read data, the author assembled 4142 microbial metagenome-assembled genomes (MAG), 4015 (96.93%) of which appear to correspond to new species and 13 circular whole-chromosome bacterial genomes representing novel species. Metagenomics sequencing technology can identify a large number of previously unknown bacterial species in intestinal microorganisms and has been used to characterize the functions of these microorganisms at the genomic level. The author further analyzed the similarity between the predicted CAZymes and the current CAZy database, and found that 187429 of the predicted proteins were new CAZy. It was also found that the identification of new CAZy and potential cellulose-degrading bacteria contributed to a better understanding of carbohydrate metabolism in the horse gut, and provided a rich source of new enzymes and microorganisms for the fermentation biotechnology industry. Additionally, this study also revealed the resistance characteristics and microorganisms related to athletic performance in horses. This study provides a detailed catalog of horse gut MAGs and answers important questions about the relationship between horse gut microbiome and horse performance.

Fig. 2 Assembly of the first complete, circularized genomes from long-read data

Application of Metagenomics in Clinical Therapy

The composition of the intestinal microbiota is related to the clinical response to immune checkpoint inhibitor (ICI) treatment, but there is still a lack of recognition of specific microbiota characteristics related to the clinical benefits of ICIs. Recent study performed shotgun metagenomic sequencing of stool samples collected before ICI initiation from five observational cohorts recruiting ICI-naive patients with advanced cutaneous melanoma (n = 165). Integrating this dataset with 147 previously published metagenomics samples revealed a cohort dependent correlation between gut microbiome and responses to ICIs. Machine learning analysis confirmed the association between microbiome and overall remission rates (ORRs) and progression free survival (PFS) for ICIs, but also revealed limited repeatability of microbiome -based characteristics in different cohorts. The role of human intestinal microbiomes in the ICI response appears to be more complex than previously thought, efforts should be continued to be made to conduct metagenomic research on a larger scale, improve the representation of different populations, while controlling clinical covariates and ensuring that samples are collected and processed in the same manner and using the same technology in the future.

Figure 3. Association between the gut microbiome and response in the PRiMM-NL and PRiMM-uK cohorts
Figure 4. Comprehensive analysis of cross cohort reaction microbiome associations for newly sequenced and publicly available datasets.

Metagenomics is booming. Using sequencing technology to explore the mysteries of intestinal flora will reveal more mechanisms of intestinal diseases in the future.


  1. Chen, Liang et al. "Short- and long-read metagenomics expand individualized structural variations in gut microbiomes." Nature communications vol. 13,1 3175. 8 Jun. 2022.
  2. Li, Cunyuan et al. "Expanded catalogue of metagenome-assembled genomes reveals resistome characteristics and athletic performance-associated microbes in horse." Microbiome vol. 11,1 7. 12 Jan. 2023
  3. Lee, Karla A et al. "Cross-cohort gut microbiome associations with immune checkpoint inhibitor response in advanced melanoma." Nature medicine vol. 
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