Longitudinal shift in diabetic wound microbiota correlates with prolonged skin defense response

Abstract

Diabetics frequently suffer from chronic, nonhealing wounds. Although bacterial colonization and/or infection are generally acknowledged to negatively impact wound healing, the precise relationship between the microbial community and impaired wound healing remains unclear. Because the host cutaneous defense response is proposed to play a key role in modulating microbial colonization, we longitudinally examined the diabetic wound microbiome in tandem with host tissue gene expression. By sequencing 16S ribosomal RNA genes, we show that a longitudinal selective shift in wound microbiota coincides with impaired healing in diabetic mice (Lepr(db/db); db/db). We demonstrate a parallel shift in longitudinal gene expression that occurs in a cluster of genes related to the immune response. Further, we establish a correlation between relative abundance of Staphylococcus spp. and the expression of cutaneous defense response genes. Our data demonstrate that integrating two types of global datasets lends a better understanding to the dynamics governing host-microbe interactions.

Fig. 1.

Relative mean abundance of major bacterial genera at each time point in db/+ control mice and db/db diabetic mice (n = 10 mice of each genotype). x axis represents each time point in days. y axis is relative abundance (percentage) of bacterial genera. Superscripts on legend indicate day at which there is a statistically significant shift in that bacterial group (Mann–Whitney test; P < 0.05).

Fig. 2.

Impaired wound healing phenotype in db/db mice. (A) Depicted is a 6-mm excisional wound as it heals over 28 d. The same db/+ and db/db mouse are depicted at each time point. (B) Average measurement of wound surface area over 28 d (n = 10 mice of each genotype). y axis represents percentage surface area of original 6-mm wound. Error bars represent SD of the mean. Wound size differences are significant (P < 0.05, Welch's t test) on days 3, 7, 14, and 21.

Fig. 3.

Mean longitudinal microbiota diversity of db/+ and db/db mouse wounds as measured by the Shannon Diversity Index. Error bars represent SEM for n = 10 mice of each genotype. All time points are statistically significantly different between db/+ and db/db mice except for day 3 (P = 0.007, 0.026, 2.7 × 10⁻⁷, 5.3 × 10⁻⁸, and 0.001, respectively, by the Welch's t test).

Fig. 4.

Prolonged expression of genes corresponding to GO biological processes IR, DR, and WR. (A) Hierarchical cluster analysis of the 10 sample types (n = 4 mice of each genotype at five time points) with respect to IR genes. (B) The mRNA expression changes in IR, DR, and WR genes represented by a clustered heatmap. Red values indicate an increased expression relative to day 0, and green values indicate a decreased expression relative to day 0. A large subset of genes, indicated by the bracket, whose expression increases immediately in response to wounding in both db/+ and db/db mice shows an extended expression pattern in the db/db mice. These genes return to baseline expression levels by day 14 in db/+ wounds, but they do not return to baseline levels even at day 21 in db/db wounds.

Fig. 5.

Positive correlation between expression of cutaneous host–defense genes and Staphylococcus relative abundance. The relative abundance of Staphylococcus at the wound site in db/+ (A, red) and db/db (B, blue) mice are shown during the wound time course. Using Gene Set Enrichment Analysis, the GO biological processes IR, DR, and WR are significantly enriched among those genes whose expression is most positively correlated with Staphylococcus abundance. Leading edge subset analysis was used to extract the 258 genes contributing to this enrichment. The longitudinal expression of these 258 genes is shown for db/+ (C, red) and db/db (D, blue) mice. The median expression of these genes is shown for db/+ (E, red) and db/db (F, blue) mice.