Functional and Taxonomic Traits of the Gut Microbiota in Type 1 Diabetes Children at the Onset: A Metaproteomic Study

Abstract

Type 1 diabetes (T1D) is a chronic autoimmune metabolic disorder with onset in pediatric/adolescent age, characterized by insufficient insulin production, due to a progressive destruction of pancreatic β-cells. Evidence on the correlation between the human gut microbiota (GM) composition and T1D insurgence has been recently reported. In particular, 16S rRNA-based metagenomics has been intensively employed in the last decade in a number of investigations focused on GM representation in relation to a pre-disease state or to a response to clinical treatments. On the other hand, few works have been published using alternative functional omics, which is more suitable to provide a different interpretation of such a relationship. In this work, we pursued a comprehensive metaproteomic investigation on T1D children compared with a group of siblings (SIBL) and a reference control group (CTRL) composed of aged matched healthy subjects, with the aim of finding features in the T1D patients' GM to be related with the onset of the disease. Modulated metaproteins were found either by comparing T1D with CTRL and SIBL or by stratifying T1D by insulin need (IN), as a proxy of β-cells damage, showing some functional and taxonomic traits of the GM, possibly related to the disease onset at different stages of severity.

Keywords: Type 1 diabetes; functional annotation; gut microbiota; insulin need; label-free quantitative analysis (LFQ); metaproteomics; paediatric.

Figure 1

Analysis of GM ecology comparing the T1D, SIBL, and CTRL groups. Panel (A): Alpha diversity was calculated with QIIME using the Shannon diversity index and determining the p-value for group comparison by variance analysis (ANOVA). Significance (marked with *** when p-value < 0.01) was found for the comparisons between the T1D and SIBL groups (p-value = 0.009) and between CTRL and SIBL (p-value = 0.002). Panel (B): Principal coordinate analysis (PCoA) plots were constructed to illustrate the beta diversity of the samples, based on the Bray–Curtis distance matrix. To test the association between the covariates and beta diversity measures, a variance analysis method based on permutation was used (PERMANOVA, 9999 permutations, p-value = 0.0014).

Figure 2

Bar charts plotting the number of statistically significant differential PGs, determined by the abundance ratio values in the comparison between groups of individuals and associated with functional annotation. Color code identifies taxa assigned to UP- (right) and DOWN-regulated (left) PGs by LCA. Selected COG categories: [C] Energy production and conversion—[E] Amino acid transport and metabolism—[F] Nucleotide transport and metabolism—[G] Carbohydrate transport and metabolism—[H] Coenzyme transport and metabolism—[I] Lipid transport and metabolism—[M] Cell wall/membrane/envelope biogenesis—[O] Posttranslational modification, protein turnover, chaperones—[P] Inorganic ion transport and metabolism—[R] General function prediction only—[U] Intracellular trafficking,secretion, and vesicular transport. Panels (A–C): comparisons between T1D, CTRL, and SIBL groups. Panel (D): comparison between groups of patients stratified by severity (T1D-A and T1D-B). Panels (E,F): tests comparing T1D-A and T1D-B groups versus CTRL. Panels (G,H): tests comparing T1D-A and T1D-B groups versus SIBL.

Figure 3

Bar charts plotting the number of statistically significant differential PGs, determined by the abundance ratio values in the comparison between groups of individuals and associated with functional annotation. Color code identifies taxa assigned to UP- (right) and DOWN-regulated (left) PGs by LCA. Selected pathways from the KEGG DB: [1] ABC transporters—[2] Alanine, aspartate, and glutamate metabolism—[3] Aminoacyl-tRNA biosynthesis—[4] Fatty acid degradation—[5] Fructose and mannose metabolism—[6] Galactose metabolism—[7] Glycolysis/Gluconeogenesis—[8] Oxidative Phosphorylation—[9] Pentose and glucoronate interconversion—[10] Pentose phosphate pathway—[11] Purine metabolism—[12] Pyrimidine metabolism—[13] Pyruvate metabolism—[14] Starch and sucrose metabolism. Panels (A–C): comparisons between T1D, CTRL, and SIBL groups. Panel (D): comparison between groups of patients stratified by severity (T1D-A and T1D-B). Panels (E,F): tests comparing T1D-A and T1D-B groups versus CTRL. Panels (G,H): tests comparing T1D-A and T1D-B groups versus SIBL.

Figure 4

Scheme evidencing the detected up- and down-regulated bacterial functions involved in the butyrate pathway through Acetyl-CoA in the GM of T1D children when compared with that of healthy CTRL.