Utilizing a reductionist model to study host-microbe interactions in intestinal inflammation.

BACKGROUND: The gut microbiome is altered in patients with inflammatory bowel disease, yet how these alterations contribute to intestinal inflammation is poorly understood. Murine models have demonstrated the importance of the microbiome in colitis since colitis fails to develop in many genetically susceptible animal models when re-derived into germ-free environments. We have previously shown that Wiskott-Aldrich syndrome protein (WASP)-deficient mice (Was-/-) develop spontaneous colitis, similar to human patients with loss-of-function mutations in WAS. Furthermore, we showed that the development of colitis in Was-/- mice is Helicobacter dependent. Here, we utilized a reductionist model coupled with multi-omics approaches to study the role of host-microbe interactions in intestinal inflammation. RESULTS: Was-/- mice colonized with both altered Schaedler flora (ASF) and Helicobacter developed colitis, while those colonized with either ASF or Helicobacter alone did not. In Was-/- mice, Helicobacter relative abundance was positively correlated with fecal lipocalin-2 (LCN2), a marker of intestinal inflammation. In contrast, WT mice colonized with ASF and Helicobacter were free of inflammation and strikingly, Helicobacter relative abundance was negatively correlated with LCN2. In Was-/- colons, bacteria breach the mucus layer, and the mucosal relative abundance of ASF457 Mucispirillum schaedleri was positively correlated with fecal LCN2. Meta-transcriptomic analyses revealed that ASF457 had higher expression of genes predicted to enhance fitness and immunogenicity in Was-/- compared to WT mice. In contrast, ASF519 Parabacteroides goldsteinii's relative abundance was negatively correlated with LCN2 in Was-/- mice, and transcriptional analyses showed lower expression of genes predicted to facilitate stress adaptation by ASF519 in Was-/-compared to WT mice. CONCLUSIONS: These studies indicate that the effect of a microbe on the immune system can be context dependent, with the same bacteria eliciting a tolerogenic response under homeostatic conditions but promoting inflammation in immune-dysregulated hosts. Furthermore, in inflamed environments, some bacteria up-regulate genes that enhance their fitness and immunogenicity, while other bacteria are less able to adapt and decrease in abundance. These findings highlight the importance of studying host-microbe interactions in different contexts and considering how the transcriptional profile and fitness of bacteria may change in different hosts when developing microbiota-based therapeutics. Video abstract.

Modeling the Effect of Mucin Binding in the Gut on Drug Delivery.

An important part the absorption, distribution, metabolism and excretion of an oral therapeutic is the flux rate of drug compound crossing the mucus lining of the gut. To understand this part of the absorption process, we develop a mathematical model of advection, diffusion and binding of drug compounds within the mucus layer of the intestines. Analysis of this model yields simple, measurable criteria for the successful mucin layer traversal of drug compound.

Principled Structured Incorporation of Clinical Knowledge Into Strategic Development Decisions.

Efficient use of limited pharmaceutical product development resources requires integrating multiple attributes, such as efficacy, safety, pharmacology, and so on, to decide at any stage whether the development of a product should proceed aggressively or slowly or be terminated. The decision process proceeds most effectively when the knowledge and experience of a product development team are transparently and reproducibly integrated with the findings from completed experiments and trials. In this article, the authors describe an approach for quantitatively and objectively assessing evidence at any stage of development, one based on a mathematical combination of sets of pairwise comparisons. The attributes of the process and the rules for combining its elements to guide decisions are determined by the project team and other stakeholders before obtaining the determinative data to facilitate exploration of the sensitivity of a recommended action to various assumptions. Its statistical properties can be evaluated with standard statistical decision analysis methods.

Modeling effect of a γ-secretase inhibitor on amyloid-ß dynamics reveals significant role of an amyloid clearance mechanism.

Aggregation of the small peptide amyloid beta (Aß) into oligomers and fibrils in the brain is believed to be a precursor to Alzheimer's disease. Aß is produced via multiple proteolytic cleavages of amyloid precursor protein (APP), mediated by the enzymes ß- and γ-secretase. In this study, we examine the temporal dynamics of soluble (unaggregated) Aß in the plasma and cerebral-spinal fluid (CSF) of rhesus monkeys treated with different oral doses of a γ-secretase inhibitor. A dose-dependent reduction of Aß concentration was observed within hours of drug ingestion, for all doses tested. Aß concentration in the CSF returned to its predrug level over the monitoring period. In contrast, Aß concentration in the plasma exhibited an unexpected overshoot to as high as 200% of the predrug concentration, and this overshoot persisted as late as 72 hours post-drug ingestion. To account for these observations, we proposed and analyzed a minimal physiological model for Aß dynamics that could fit the data. Our analysis suggests that the overshoot arises from the attenuation of an Aß clearance mechanism, possibly due to the inhibitor. Our model predicts that the efficacy of Aß clearance recovers to its basal (pretreatment) value with a characteristic time of >48 hours, matching the time-scale of the overshoot. These results point to the need for a more detailed investigation of soluble Aß clearance mechanisms and their interaction with Aß-reducing drugs.

A novel 3-dimensional micro-ultrasound approach to automated measurement of carotid arterial plaque volume as a biomarker for experimental atherosclerosis.

Improved methods for non-invasive in vivo assessment are needed to guide development of animal models of atherosclerosis and to evaluate target engagement and in vivo efficacy of new drugs. Using novel 3D-micro-ultrasound technology, we developed and validated a novel protocol for 3D acquisition and analysis of imaging to follow lesion progression in atherosclerotic mice. The carotid arteries of ApoE receptor knockout mice and normal control mice were imaged within the proximal 2mm from the aortic branch point. Plaque volume along that length was quantified using a semi-automated 3D segmentation algorithm. Volumes derived by this method were compared to those calculated using 3-D histology post-mortem. Bland-Altman comparison revealed close correlation between these two measures of plaque volume. Furthermore, using a segmentation technique that captures early positive and 33 week negative remodeling, we found evidence that plaque volume increases linearly over time. Each animal and each plaque served as its own control, allowing accurate comparison. The high fidelity anatomical registration of this protocol provides increased spatial resolution and therefore greater sensitivity for measurement of plaque wall size, an advance over 2-dimensional measures of intimal-medial-thickening. Further, 3-dimensional analysis ensures a point of registration that captures functional markers in addition to the standard structural markers that characterize experimental atherosclerosis. In conclusion, this novel imaging protocol provides a non-invasive, accurate surrogate marker for experimental atherosclerosis over the life of the entire lesion.