The second phase of the 10-year National Institutes of Health-funded Human Microbiome Project, the Integrative Human Microbiome Project, has recently been completed and provides a useful repository of microbiome-related data, tools and protocols for the research community.
The two studies featured in this post have characterized host-microbiome interactions through longitudinal sampling in inflammatory bowel diseases (IBDs) and prediabetes. Although some of reported shifts in the composition and function of the microbiome were reported in previous studies, the use of multi-omic technologies has allowed for the discovery of new host-microbiome interactions.
The multi-omic profiling of 2,965 stool, biopsy, and blood specimens from 132 pediatric and adult individuals followed with either Crohn’s disease, ulcerative colitis or who did not have IBD identified taxa, expressed functions, IBD-linked metabolites and host gene expression disrupted in the gut during increased disease activity over the space of a year.
At the taxonomic level, an unclassified Subdoligranulum species was markedly reduced in participants with IBD and may contribute, alongside a reduction in butyrate producers, to the carnitine and bile acid dysregulation observed. Other metabolites such as nicotinuric acid were present in participants with IBD and distinguished them from controls.
The involvement of the host and gut microbiome in IBD activity was also supported by an increase in facultative anaerobes, alterations in transcription for several microbial species such as clostridia, and increased levels of antibodies in host serum.
Among them, changes in the metabolome—mainly methylimidazole acetic acid and urate—explained the more frequent and extreme temporal shifts in the gut microbiome in participants with IBD compared with controls that did not have IBD.
On the other hand, the study of 106 healthy individuals and individuals with prediabetes explored host (plasma proteomics and metabolomics, exomes and transcriptomes in peripheral blood mononuclear cells, glucose dysregulation tests and weight) and microbial (16S sequencing and metagenomics) features over 4 years and during periods of health and perturbations, including respiratory viral infections and directed weight gain and weight loss.
Although baseline measurements tended to maintain stable within individuals, clinical laboratory measurements, cytokine profiles and low abundance microbial taxa were highly variable between participants.
Specifically, participants who developed insulin resistance had distinguishable molecular and microbial patterns at baseline compared with participants who were insulin-sensitive. This was accompanied by differential responses to respiratory viral infections and weight loss depending on whether a participant was insulin sensitive or insulin resistant.
While insulin-resistant participants showed a reduced response to respiratory viral infections, more chronic inflammation and altered lipid metabolism, insulin-sensitive participants were responsive to respiratory viral infections through a proper activation of acute phase response pathways.
As different clinical and biochemical parameters together with gut microbial changes shaped glucose dysregulation over the study period, such results suggest the need for taking into account different measurements for better managing patients’ health.
On the whole, these findings reveal that molecular and microbial profiles tend to be personalized and differ between insulin-resistant individuals and insulin-sensitive participants both at baseline and in response to periods of respiratory viral infections and weight loss.
These results provide an in-depth description of the host and microbial activities involved in inflammatory bowel diseases and prediabetes and help create databases with resources for researchers and even for use in the clinical setting. Moving from descriptive microbiome sequencing studies to multi-omics approaches that integrate both host and microbial responses gives a better understanding of overall host-microbiome dynamics that may pave the way to predicting disease events.
References:
Lloyd-Price J, Arze C, Ananthakrishnan AN, et al. Multi-omics of the gut microbial ecosystem in inflammatory bowel diseases. Nature. 2019; 569(7758):655-662. doi: 10.1038/s41586-019-1237-9.
Zhou W, Sailani MR, Contrepois K, et al. Longitudinal multi-omics of host-microbe dynamics in prediabetes. Nature. 2019; 569(7758):663-71. doi: 10.1038/s41586-019-1236-x.
