Impaired host response and the presence of Acinetobacter baumannii in the serum microbiome of type-II diabetic patients

Abstract

Type II diabetes (T2D) affects over 10% of the US population and is a growing disease worldwide that manifests with numerous comorbidities and defects in inflammation. This dysbiotic host response allows for infection of the host by numerous microorganisms. In the course of T2D disease, individuals can develop chronic infections including foot ulcers and periodontitis, which lead to further complications and opportunistic infections in multiple body sites. In this study, we investigated the serum of healthy subjects and patients with T2D with (T2DP) or without periodontitis for both microbiome signatures in addition to cytokine profiles. Surprisingly, we detected the presence of Acinetobacter baumanii in the serum of 23% individuals with T2D/T2DP tested. In T2DP, IL-1β, TNF-α, MCP-1, IL-6, IL-8, and IFN-γ were significantly elevated in ABC-positive subjects. As an emerging pathogen, A. baumanii infection represents a risk for impaired inflammation and the development of comorbidities in subjects with T2D.

Keywords: Human Metabolism; Microbiology.

Graphical abstract

Figure 1

16S alpha and beta diversity of serum microbiomes changes with subject status (A–C) Species richness is displayed based on Faith's phylogenetic diversity (Faith, 1992) (A), and species evenness is based on Pielou's evenness index (Pielou, 1966) (B) for healthy, type-II diabetic patients (T2D), and type-II diabetic patients with periodontitis (T2DP) samples. Significance was determined by Kruskal-Wallis analysis of variance (Kruskal and Wallis, 1952) for each comparison indicated, and Benjamini-Hochberg correction (Benjamini and Hochberg, 1995) was applied to generate adjusted q-values. All data used were strictly filtered based on no-template control indexes. ∗q-value < 0.002 compared with healthy, ∗∗q-value < 0.0004 compared with healthy and with T2D. (C) Beta diversity Bray-Curtis distances. Pairwise PERMANOVA of each category versus each (group size of 3, n = 112) was performed in 999 permutations. ∗∗∗q-value differs from “healthy” < 0.001. See also Figure S4.

Figure 2

Phylum-level diversity changes between subject status (A and B) DADA2-analyzed data were aligned to the SILVA database for taxonomical assignment via QIIME2 as described in Methods. Data from both sequencing runs were collapsed to phylum-level taxa and displayed for (A) strict filtered and (B) minimally filtered conditions. Asterisks on the top indicate run-run sample pairs that were positive for A. baumanii.

Figure 3

Healthy subjects versus all subjects with T2D reveal a potential enrichment of A. baumanii Initial minimal entropy decomposition (MED) analysis of 16S data with taxonomy assigned based on RDP database alignment to generate species-level assignments was performed followed by linear discriminate analysis effect size quantification (LEfSe). This revealed enrichment of several species/genera in subjects with T2D relative to healthy. DADA2 analysis of the same dataset was aligned to the SILVA database and shows similar patterns of enrichment (see also Figure S5).

Figure 4

Beta diversity quantification between subject groups (A and B) SILVA-assigned taxonomy of DADA2-analyzed 16S data was used to determine Bray-Curtis dissimilarity between samples for strictly filtered (A) and minimally filtered (B) data. Non-metric multidimensional scaling and statistical analysis for each subject group was performed in R using the vegan package as described in Methods. p-value of 0.001 determined by PERMANOVA test via the adonis2 function.

Figure 5

Clone library design to verify ABC complex member identity Amplification with oMR328-329 primers produced an amplicon between 120 and 1306 bp of the A. baumanii 16S rDNA sequence. This allowed for Sanger sequencing of information-rich nucleotides indicated above allowing for species differentiation beyond initial V1-V3 sequencing with the 27F-519R primers. The table beneath indicated the total number of individual clones sequenced per sample and which species they aligned to with 100% identity in the NCBI non-redundant database.

Figure 6

Cytokine profile quantification reveals distinct differences between subject groupings and A. baumanii (ABC) presence Heatmap showing immune mediator concentrations derived from serum of diabetic and healthy samples were compared to understand the role of ABC in each sample group. (I) Diabetic/Healthy, (II) All ABC+/All ABC-, (III) ABC+ Diabetic/ABC- Diabetic, (IV) ABC+ Diabetic/Healthy, (V) ABC- Diabetic/Healthy. Data are clustered according to comparison groups (red, highest expression; yellow, lowest expression). Hierarchical clustering was employed by Morpheus from the Broad Institute (Morpheus, https://software.broadinstitute.org/morpheus). Observations from hierarchical clustering are shown in a tree, with ABC groups highlighted in the box. ABC+ groups (II, III, and IV) showed significantly different (p < 0.01) levels of IL-1β, IL-6, IL-8, MCP-1, IFN- γ. ∗p value <0.01 between groups via unpaired Student's t test (red, highest expression; yellow, lowest expression).

Figure 7

Host-microbial correlation-resolved type-II diabetic associations with inflammatory cytokines HOMD/RDP assigned taxonomy of MED-analyzed 16S data for both T2D and T2DP samples and cytokine concentrations were analyzed via Pearson correlation coefficient in R using the rcorr function. Significance was determined using the asymptotic p values generated by rcorr with ∗p value <0.05, ∗∗p value <0.01. Data are strictly filtered with taxa present in no-template controls subtracted. See also Figures S6, S8, and S9.