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Volkers, L.

Publications and source records attributed to Volkers, L..

2 recordsLinked to original sources

Dynamic Loading of Human Engineered Heart Tissue Enhances Contractile Function and Drives Desmosome-linked Disease Phenotype

The role mechanical forces play in shaping the structure and function of the heart is critical to understanding heart formation and the etiology of disease but is challenging to study in patients. Engineered heart tissues (EHTs) incorporating human induced pluripotent stem cell (hiPSC)-derived cardiomyocytes have the potential to provide insight into these adaptive and maladaptive changes in the heart. However, most EHT systems are unable to model both preload (stretch during chamber filling) and afterload (pressure the heart must work against to eject blood). Here, we have developed a new dynamic EHT (dyn-EHT) model that enables us to tune preload and have unconstrained fractional shortening of >10%. To do this, 3D EHTs are integrated with an elastic polydimethylsiloxane (PDMS) strip that provides mechanical pre- and afterload to the tissue in addition to enabling contractile force measurements based on strip bending. Our results demonstrate in wild-type EHTs that dynamic loading is beneficial based on the magnitude of the forces, leading to improved alignment, conduction velocity, and contractility. For disease modeling, we use hiPSC-derived cardiomyocytes from a patient with arrhythmogenic cardiomyopathy (ACM) due to mutations in desmoplakin. We demonstrate that manifestation of this desmosome-linked disease state requires the dyn-EHT conditioning and that it cannot be induced using 2D or standard 3D EHT approaches. Thus, dynamic loading strategy is necessary to provoke a disease phenotype (diastolic lengthening, reduction of desmosome counts, and reduced contractility), which are akin to primary endpoints of clinical disease, such as chamber thinning and reduced cardiac output. Single Sentence SummaryDevelopment of a dynamic mechanical loading platform to improve contractile function of engineered heart tissues and study cardiac disease progression.

bioengineering

NaV1.1 and NaV1.6 selective compounds reduce the behavior phenotype in a novel zebrafish model for Dravet Syndrome

Dravet syndrome is caused by dominant loss-of-function mutations in SCN1A which cause reduced activity of Nav1.1 leading to lack of neuronal inhibition. On the other hand, gain-of-function mutations in SCN8A can lead to a severe epileptic encephalopathy subtype by over activating NaV1.6 channels. These observations suggest that Nav1.1 and Nav1.6 represent two opposing sides of the neuronal balance between inhibition and activation. Here, we hypothesize that Dravet syndrome may be treated by either enhancing Nav1.1 or reducing Nav1.6 activity. To test this hypothesis we generated and characterized a novel DS zebrafish model and tested new compounds that selectively activate or inhibit the human NaV1.1 or NaV1.6 channel respectively. We used CRISPR/Cas9 to generate two separate Scn1Lab knockout lines as an alternative to previous knock-down models. Using an optimized locomotor assay, spontaneous burst movements were detected that were unique to Scn1Lab knockouts and disappear when introducing human SCN1A mRNA. Besides the behavioral phenotype, Scn1Lab knockouts show sudden, electrical discharges in the brain that indicate epileptic seizures in zebrafish. Scn1Lab knockouts showed increased sensitivity to the convulsant pentylenetetrazole and a reduction in whole organism GABA levels. Drug screenings further validated a Dravet syndrome phenotype. We tested the NaV1.1 activator AA43279 and our newly synthesized NaV1.6 inhibitors MV1369 and MV1312 in the Scn1Lab knockouts. Both type of compounds significantly reduced the number of burst movements. Our results show that selective inhibition of NaV1.6 could be just as efficient as selective activation of NaV1.1 and these approaches could prove to be novel potential treatment strategies for Dravet syndrome and other (genetic) epilepsies. Compounds tested in zebrafish however, should always be further validated in other model systems, preferably human derived.

genetics