Clearance of bacterial infections poses great challenges for the vertebrate host. While there is an obvious need to rapidly eradicate bacteria from the infection site, unnecessary collateral tissue damage associated with inflammation must be avoided. This requires a balanced response, which is likely to change its character during different phases of the infection process. Results from the transcriptomics analysis corroborated this reasoning. The significance of transcriptional responses at different time points, measured as adjusted P-values, correlated to the progression of infection. Low significance was obtained 3 h post-infection when few bacteria were present in the proximal tubule and no apparent tissue damage was observed. In contrast, statistically significant data were generated 8 h post-infection when bacteria had efficiently colonized the tubule and immune cells had infiltrated the site. Our previous findings, based on intravital imaging and physiological recordings, demonstrate however that pronounced local tissue activities already occur within the first 3-4 h of infection [6, 10]. This discrepancy may reflect the difficulty to apply a transcriptomics approach to complex tissues, and explains why it has preferentially been used in in vitro cell culture systems.
The infection protocol used in this paper was based on administration of washed overnight UPEC cultures. Clearly, such a culture includes a fraction of dead bacteria and LPS in addition to the live UPEC. Initially, LPS and dead bacteria may interact/bind to the epithelium, thereby inducing an inflammatory response. However, with the rapid growth of live bacteria these effects must be considered transient in the perspective of our analysis.
Appropriate biopsies for the study of dynamic tissue responses demand a strict control of the infection in space and time. In the current rat model, only one out of ca. 30,000 nephrons is infected. The infected nephron must be analyzed together with some immediately surrounding tissue to allow inclusion of peritubular capillaries and cells extravasated from the blood stream. Dissected biopsies contained ~1,500 uninfected nephrons in addition to the infected one. Yet, the microarray analysis identified 59 genes to be differentially expressed 8 h post-infection. In light of the vast number of uninfected nephrons, sheer detection of differential expression implies that cells in and around the bacteria-exposed nephron elicit a strong response to infection. Most of the differentially expressed genes were found to be upregulated. This may be attributed to the steady state gene expression in the uninfected nephrons, which may efficiently mask any downregulation. Also, mRNA from recruited immune cells contributes specifically to the pool of upregulated genes. Thus, the few downregulated genes identified in this study may result from a general downregulation in cells throughout the renal cortex.
Functional classification revealed an overrepresentation of differentially expressed genes in GO categories related to the "immune response". Although not a surprising result, it illustrates the validity of our approach. A previous finding, showing that ischemia is induced as a host response during renal colonization , was corroborated by the present analysis, as genes coding for proteins involved in wound healing and hypoxia were identified. This, and the fact that numerous genes involved in "biological regulation" were identified, underscores the complexity of the tissue response to infection.
Comparative transcriptomics can be used to retrieve information from microarray data sets that are of too low significance when treated individually. The power of comparative transcriptomics was shown by Jenner and Young when they, based on 32 studies involving 77 different types of host-pathogen interactions, defined 511 genes as a 'Generic alarm signal' to infection . The present analysis applied more stringent parameters when selecting data sets. This may explain why the common core of "General tissue response to early local bacterial infections" was limited to 80 genes. While 39 of these genes also were present in the core of 'Generic alarm signal', 41 were not. The latter group may represent a response specifically obtained in the live animal model of infection, in the presence of all influencing physiological factors.
Using comparative transcriptomics, significant data could also be retrieved from the 5 h data set, both by comparing to the 8 h data set, and by building a core out of the 5 h data set and data sets b-d. Approximately 60 genes were differentially expressed at both 5 h and 8 h post-infection. The 5 h post-infection core of "General tissue response to early local bacterial infections" included 31 genes. This indicates that a significant induction occurs already at 5 h post-infection that is maintained over the following hours. In contrast, a sub-set of genes in the 5 h core were not induced at 8 h, which suggests a short-lived, time-dependent activation. Collectively, this demonstrates the feasibility of the present approach to study the dynamics of tissue responses during infection.
Closer inspection of the common core of "General tissue response to early local bacterial infections" revealed that ca 25% of the genes was associated to IFN-γ responses. IFN-γ is a key mediator of inflammation and immunity, controlling the balance between bacterial clearance on the one hand, and limitation of tissue damage as a consequence of inflammation on the other . As the common core predicted, we could detect significant amounts of IFN-γ in the systemic circulation of rats with an ongoing local kidney infection. Several roles for systemic IFN-γ have been reported. Immune cells, such as neutrophils and monocytes, become primed already in the bloodstream, and may therefore act more efficiently once they reach the site of infection . For example, IFN-γ activates neutrophil defense systems, such as phagocytosis and production of reactive oxygen species [35, 36], as well as induction of monocyte- and T cell-attracting chemokine production . Conversely, systemic IFN-γ is also known to downregulate IL-8 and matrix metalloproteinase production, thereby downregulating recruitment of neutrophils [34, 35]. Thus, systemic IFN-γ may have dual roles in the UPEC infection, balancing the appropriate inflammatory response while restricting tissue damage.
At present, we can only speculate about the inter-organ communication leading to splenic IFN-γ production. The infection kinetics of the local infection may limit the recruitment of IFN-γ producing cells into the renal tissue. It is thus unlikely that the infected kidney acts as the source for serum IFN-γ. Yet, the attracted immune cells will participate in the production of other cytokines, which may act as triggers for IFN-γ production. We excluded the classical IFN-γ inducing cytokine IL-12, since Il12a transcripts were not upregulated in either kidney or spleen. Instead, our results suggest a possible signaling cascade where a local renal IL-23 production induces IFN-γ in the spleen. IL-23 dependent IFN-γ production has previously been demonstrated by others . Alternatively, IL-23 may act indirectly via IL-17, which we found upregulated in both renal and spleen tissue. This hypothesis is supported by the finding that IL-23 induces IL-17 expression in γδ T cells in the spleen , as well as a recent report, showing IL-17 dependent IFN-γ production in a renal ischemia-reperfusion model . IL-17 has previously been shown to be involved in the host defense to urinary tract infections . Further research is however necessary to resolve a possible causality between these cytokines.
The host thus mobilizes the entire circulation even for a small infection, a process analogous to the acute phase response that affects the entire animal upon infection . We speculate that in renal infections, inter-organ communication leading to elevated systemic signals may be advantageous in preventing future infections at other sites. Numerous examples exist demonstrating the ability of the kidney to cross-talk with other organs . Acute kidney injury, i.e. ischemia, can induce inflammatory cascades in other organs leading to organ failure and mortality, sometimes within hours ( and references therein). The series of molecular events we report are also remarkably fast: between initiation of bacterial colonization and systemic presence of IFN-γ lie less than 8 h. Collectively, data presented herein highlight that gaining a full understanding of the infection process requires innate immune responses to preferentially be studied in live animal models.