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Soltisz, A. M.

Publications and source records attributed to Soltisz, A. M..

3 recordsLinked to original sources

Vascular Endothelial Barrier Protection Prevents Atrial Fibrillation by Preserving Cardiac Nanostructure

Atrial fibrillation (AF) is the most common cardiac arrhythmia, affecting [~]3% of the US population. It is widely associated with inflammation, vascular dysfunction, and elevated levels of the vascular leak-inducing cytokine, vascular endothelial growth factor (VEGF). The mechanism underlying AF is not well understood and current treatments are limited to managing this progressive disease, rather than arresting the underlying pathology. We previously identified edema-induced disruption of sodium channel (NaV1.5) -rich intercalated disk (ID) nanodomains as a novel mechanism for AF initiation secondary to acute inflammation. Therefore, we hypothesized that protecting the vascular barrier can prevent vascular leak-induced atrial arrhythmias. We identified two molecular targets for vascular barrier protection, connexin43 (Cx43) hemichannels and pannexin-1 (Panx1) channels, which have been implicated in cytokine-induced vascular leak. AF incidence was increased in untreated mice exposed to VEGF relative to vehicle controls. VEGF also increased the average number of AF episodes. VEGF shifted NaV1.5 signal to longer distances from Cx43 gap junctions (GJs), measured by a distance transformation-based spatial analysis of 3D confocal images of IDs. Similar effects were observed with NaV1.5 localized near mechanical junctions (MJs) composed of N-cad. Blocking connexin43 hemichannels (CT11 peptide) or Panx1 channels (PxIL2P peptide) significantly reduced the duration of AF episodes compared to VEGF alone with no treatment. Concurrently, both peptide therapies preserved NaV1.5 distance from GJs to control levels and reduced MJ-adjacent intermembrane distance in these hearts. Notably, similar antiarrhythmic efficacy was also achieved with clinically-relevant small molecule inhibitors of Cx43 and Panx1.

physiology↗

Spatial Pattern Analysis using Closest Events (SPACE): A Nearest Neighbor Point Pattern Analysis Framework for Assessing Spatial Relationships from Image Data

The quantitative description of biological structures is a valuable yet difficult task in the life sciences. This is commonly accomplished by imaging samples using fluorescence microscopy and analyzing resulting images using Pearsons correlation or Manders co-occurrence intensity-based colocalization paradigms. Though conceptually and computationally simple, these approaches are critically flawed due to their reliance on signal overlap, sensitivity to cursory signal qualities, and inability to differentiate true and incidental colocalization. Point pattern analysis provides a framework for quantitative characterization of spatial relationships between spatial patterns using the distances between observations rather than their overlap, thus overcoming these issues. Here we introduce an image analysis tool called Spatial Pattern Analysis using Closest Events (SPACE) that leverages nearest neighbor-based point pattern analysis to characterize the spatial relationship of fluorescence microscopy signals from image data. The utility of SPACE is demonstrated by assessing the spatial association between mRNA and cell nuclei from confocal images of cardiac myocytes. Additionally, we use synthetic and empirical images to characterize the sensitivity of SPACE to image segmentation parameters and cursory image qualities such as signal abundance and image resolution. Ultimately, SPACE delivers performance superior to traditional colocalization methods and offers a valuable addition to the microscopists toolbox.

bioengineering↗

Unraveling Chamber-specific Differences in Intercalated Disc Ultrastructure and Molecular Organization and Their Impact on Cardiac Conduction

During each heartbeat, the propagation of action potentials through the heart coordinates the contraction of billions of individual cardiomyocytes and is thus, a critical life process. Unsurprisingly, intercalated discs, which are cell-cell contact sites specialized to provide electrical and mechanical coupling between adjacent cardiomyocytes, have been the focus of much investigation. Slowed or disrupted propagation leads to potentially life-threatening arrhythmias in a wide range of pathologies, where intercalated disc remodeling is a common finding. Hence, the importance and urgency of understanding intercalated disc structure and its influence on action potential propagation. Surprisingly, however, conventional modeling approaches cannot predict changes in propagation elicited by perturbations that alter intercalated disc ultrastructure or molecular organization, owing to lack of quantitative structural data at subcellular through nano scales. In order to address this critical gap in knowledge, we sought to quantify intercalated disc structure at these finer spatial scales in the healthy adult mouse heart and relate them to function in a chamber-specific manner as a precursor to understanding the impacts of pathological intercalated disc remodeling. Using super-resolution light microscopy, electron microscopy, and computational image analysis, we provide here the first ever systematic, multiscale quantification of intercalated disc ultrastructure and molecular organization. By incorporating these data into a rule-based model of cardiac tissue with realistic intercalated disc structure, and comparing model predictions of electrical propagation with experimental measures of conduction velocity, we reveal that atrial intercalated discs can support faster conduction than their ventricular counterparts, which is normally masked by inter-chamber differences in myocyte geometry. Further, we identify key ultrastructural and molecular organization features underpinning the ability of atrial intercalated discs to support faster conduction. These data provide the first stepping stone to elucidating chamber-specific impacts of pathological intercalated disc remodeling, as occurs in many arrhythmic diseases.

physiology↗