Integrative metagenomic and metabolomic analyses reveal gut microbiota-derived multiple hits connected to development of gestational diabetes mellitus in humans

ABSTRACT

Gestational diabetes mellitus (GDM) is characterized by the development of hyperglycemia and insulin resistance during the second or third trimester of pregnancy, associated with considerable risks to both the mother and developing fetus. Although emerging evidence suggests an association between the altered gut microbiota and GDM, remarkably little is known about the microbial and metabolic mechanisms that link the dysbiosis of the gut microbiota to the development of GDM. In this study, a metagenome-wide association study and serum metabolomics profiling were performed in a cohort of pregnant women with GDM and pregnant women with normal glucose tolerance (NGT). We identified gut microbial alterations associated with GDM and linked to the changes in circulating metabolites. Blood metabolite profiles revealed that GDM patients exhibited a marked increase in 2-hydroxybutyric acid and L-alpha-aminobutyric acid, but a decrease in methionine sulfoxide, allantoin, and dopamine and dopaminergic synapse, when compared with those in NGT controls. Short-chain fatty acid-producing genera, including Faecalibacterium, Prevotella, and Streptococcus, and species Bacteroides coprophilus, Eubacterium siraeum, Faecalibacterium prausnitzii, Prevotella copri, and Prevotella stercorea, were significantly reduced in GDM patients relative to those in NGT controls. Bacterial co-occurrence network analysis revealed that pro-inflammatory bacteria were over-represented as the core species in GDM patients. These microbial and metabolic signatures are closely associated with clinical parameters of glucose metabolism in GDM patients and NGT controls. In conclusion, we identified circulating dopamine insufficiency, imbalanced production of SCFAs, and excessive metabolic inflammation as gut microbiota-driven multiple parallel hits linked to GDM development. This work might explain in part the mechanistic link between altered gut microbiota and GDM pathogenesis, and suggest that gut microbiota may serve as a promising target to intervene in GDM.

KEYWORDS:

• Glucose intolerance
• insulin resistance
• microbial metabolite
• metabolic inflammation

Research highlights

• GDM patients exhibited marked changes in blood metabolites related to dopamine insufficiency.

• Short-chain fatty acid-producing gut microbial genera were substantially reduced, but pro-inflammatory bacteria were over-represented as the core species in GDM patients.

• Microbial and metabolic signatures are closely associated with clinical parameters of glucose metabolism in GDM patients and NGT controls.

• Dual-omics analyses in this study identified dopamine insufficiency, an imbalance in SCFAs, and excessive metabolic inflammation as gut microbiota-driven multiple parallel hits linked to GDM.

Data and code availability

The datasets generated during metagenomic sequencing of fecal DNA samples have been deposited in NCBI Sequencing Read Archive (accession ID: PRJNA853814). The R analysis scripts used in this paper have been deposited at GitHub at https://github.com/JiatingH/GDM-Project. Links to the algorithms applied in the study are listed in Supplementary Table 2. The information will be publicly available at the time of publication. Other datasets from the current study are available from the corresponding author upon request.

Additional information of detailed methodology is described in Supplementary Materials section.

Authorship contribution statement

D.W.Y., J.T.H. and J.G. contributed to study design, data acquisition, and interpretation of the results and wrote the manuscript. J.G. obtained funding. D.W.Y, J.T.H., J.M.W., K.X., X.G., K.X.Y., Y.T., Y.L., and S.F.Z. contributed to subject recruitment, collection of clinical information and sample, and fecal DNA extraction. J.T.H., L.J., and X.L.R. contributed to bioinformatics analysis and data interpretation.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/19490976.2022.2154552

Additional information

Funding

This work was financially supported by the National Natural Science Foundation of China (81830113, 81922074), Shenzhen Basic Research Program (JCYJ20190808182402941), the Major basic and applied basic research projects in Guangdong Province, China (2019B030302005), the National Natural Science Foundation of China (1770849), the National Key R&D plan “Research on modernization of traditional Chinese medicine” (2018YFC1704200), and the Key Laboratory of Model Animal Phenotyping and Basic Research in Metabolic Diseases in Guangdong Province, China (2018KSYS003).