Person:

Yonker, Lael

A model of neutrophil migration across epithelia is desirable to interrogate the underlying mechanisms of neutrophilic breach of mucosal barriers. A co-culture system consisting of a polarized mucosal epithelium and human neutrophils can provide a versatile model of trans-epithelial migration in vitro, but observations are typically limited to quantification of migrated neutrophils by myeloperoxidase correlation, a destructive assay that precludes direct longitudinal study. Our laboratory has recently developed a new isotropic 1-μm resolution optical imaging technique termed micro-optical coherence tomography (μOCT) that enables 4D (x,y,z,t) visualization of neutrophils in the co-culture environment. By applying μOCT to the trans-epithelial migration model, we can robustly monitor the spatial distribution as well as the quantity of neutrophils chemotactically crossing the epithelial boundary over time. Here, we demonstrate the imaging and quantitative migration results of our system as applied to neutrophils migrating across intestinal epithelia in response to a chemoattractant. We also demonstrate that perturbation of a key molecular event known to be critical for effective neutrophil trans-epithelial migration (CD18 engagement) substantially impacts this process both qualitatively and quantitatively.

Neutrophil breach of the mucosal surface is a common pathological consequence of infection. We present an advanced co-culture model to explore neutrophil transepithelial migration utilizing airway mucosal barriers differentiated from primary human airway basal cells and examined by advanced imaging. Human airway basal cells were differentiated and cultured at air-liquid interface (ALI) on the underside of 3 µm pore-sized transwells, compatible with the study of transmigrating neutrophils. Inverted ALIs exhibit beating cilia and mucus production, consistent with conventional ALIs, as visualized by micro-optical coherence tomography (µOCT). µOCT is a recently developed imaging modality with the capacity for real time two- and three-dimensional analysis of cellular events in marked detail, including neutrophil transmigratory dynamics. Further, the newly devised and imaged primary co-culture model recapitulates key molecular mechanisms that underlie bacteria-induced neutrophil transepithelial migration previously characterized using cell line-based models. Neutrophils respond to imposed chemotactic gradients, and migrate in response to Pseudomonas aeruginosa infection of primary ALI barriers through a hepoxilin A3-directed mechanism. This primary cell-based co-culture system combined with µOCT imaging offers significant opportunity to probe, in great detail, micro-anatomical and mechanistic features of bacteria-induced neutrophil transepithelial migration and other important immunological and physiological processes at the mucosal surface.

Excessive neutrophil infiltration of the lungs is a common contributor to immune-related pathology in many pulmonary disease states. In response to pathogenic infection, airway epithelial cells produce hepoxilin A3 (HXA3), initiating neutrophil transepithelial migration. Migrated neutrophils amplify this recruitment by producing a secondary gradient of leukotriene B4 (LTB4). We sought to determine whether this two-step eicosanoid chemoattractant mechanism could be exploited by the pathogen Pseudomonas aeruginosa. ExoU, a P. aeruginosa cytotoxin, exhibits phospholipase A2 (PLA2) activity in eukaryotic hosts, an enzyme critical for generation of certain eicosanoids. Using in vitro and in vivo models of neutrophil transepithelial migration, we evaluated the impact of ExoU expression on eicosanoid generation and function. We conclude that ExoU, by virtue of its PLA2 activity, augments and compensates for endogenous host neutrophil cPLA2α function, leading to enhanced transepithelial migration. This suggests that ExoU expression in P. aeruginosa can circumvent immune regulation at key signaling checkpoints in the neutrophil, resulting in exacerbated neutrophil recruitment.

Common variable immunodeficiency (CVID) is increasingly recognized for its association with autoimmune and inflammatory complications. Despite recent advances in immunophenotypic and genetic discovery, clinical care of CVID remains limited by our inability to accurately model risk for non-infectious disease development. Herein, we demonstrate the utility of unbiased network clustering as a novel method to analyze inter-relationships between non-infectious disease outcomes in CVID using databases at the United States Immunodeficiency Network (USIDNET), the centralized immunodeficiency registry of the United States, and Partners, a tertiary care network in Boston, MA, USA, with a shared electronic medical record amenable to natural language processing. Immunophenotypes were comparable in terms of native antibody deficiencies, low titer response to pneumococcus, and B cell maturation arrest. However, recorded non-infectious disease outcomes were more substantial in the Partners cohort across the spectrum of lymphoproliferation, cytopenias, autoimmunity, atopy, and malignancy. Using unbiased network clustering to analyze 34 non-infectious disease outcomes in the Partners cohort, we further identified unique patterns of lymphoproliferative (two clusters), autoimmune (two clusters), and atopic (one cluster) disease that were defined as CVID non-infectious endotypes according to discrete and non-overlapping immunophenotypes. Markers were both previously described {high serum IgE in the atopic cluster [odds ratio (OR) 6.5] and low class-switched memory B cells in the total lymphoproliferative cluster (OR 9.2)} and novel [low serum C3 in the total lymphoproliferative cluster (OR 5.1)]. Mortality risk in the Partners cohort was significantly associated with individual non-infectious disease outcomes as well as lymphoproliferative cluster 2, specifically (OR 5.9). In contrast, unbiased network clustering failed to associate known comorbidities in the adult USIDNET cohort. Together, these data suggest that unbiased network clustering can be used in CVID to redefine non-infectious disease inter-relationships; however, applicability may be limited to datasets well annotated through mechanisms such as natural language processing. The lymphoproliferative, autoimmune, and atopic Partners CVID endotypes herein described can be used moving forward to streamline genetic and biomarker discovery and to facilitate early screening and intervention in CVID patients at highest risk for autoimmune and inflammatory progression.