Transient pacing in pigs with complete heart block via myocardial injection of mRNA coding for the T-box transcription factor 18.

The adenovirus-mediated somatic transfer of the embryonic T-box transcription factor 18 (TBX18) gene can convert chamber cardiomyocytes into induced pacemaker cells. However, the translation of therapeutic TBX18-induced cardiac pacing faces safety challenges. Here we show that the myocardial expression of synthetic TBX18 mRNA in animals generates de novo pacing and limits innate and inflammatory immune responses. In rats, intramyocardially injected mRNA remained localized, whereas direct myocardial injection of an adenovirus carrying a reporter gene resulted in diffuse expression and in substantial spillover to the liver, spleen and lungs. Transient expression of TBX18 mRNA in rats led to de novo automaticity and pacemaker properties and, compared with the injection of adenovirus, to substantial reductions in the expression of inflammatory genes and in activated macrophage populations. In rodent and clinically relevant porcine models of complete heart block, intramyocardially injected TBX18 mRNA provided rate-adaptive cardiac pacing for one month that strongly correlated with the animal's sinus rhythm and physical activity. TBX18 mRNA may aid the development of biological pacemakers.

An enhancer-based gene-therapy strategy for spatiotemporal control of cargoes during tissue repair.

The efficacy and safety of gene-therapy strategies for indications like tissue damage hinge on precision; yet, current methods afford little spatial or temporal control of payload delivery. Here, we find that tissue-regeneration enhancer elements (TREEs) isolated from zebrafish can direct targeted, injury-associated gene expression from viral DNA vectors delivered systemically in small and large adult mammalian species. When employed in combination with CRISPR-based epigenome editing tools in mice, zebrafish TREEs stimulated or repressed the expression of endogenous genes after ischemic myocardial infarction. Intravenously delivered recombinant AAV vectors designed with a TREE to direct a constitutively active YAP factor boosted indicators of cardiac regeneration in mice and improved the function of the injured heart. Our findings establish the application of contextual enhancer elements as a potential therapeutic platform for spatiotemporally controlled tissue regeneration in mammals.

Tbx18 Orchestrates Cytostructural Transdifferentiation of Cardiomyocytes to Pacemaker Cells by Recruiting the Epithelial-Mesenchymal Transition Program.

Previously, we reported that heterologous expression of an embryonic transcription factor, Tbx18, reprograms ventricular cardiomyocytes into induced pacemaker cells (Tbx18-iPMs), though the key pathways are unknown. Here, we have used a tandem mass tag proteomic approach to characterize the impact of Tbx18 on neonatal rat ventricular myocytes. Tbx18 expression triggered vast proteome remodeling. Tbx18-iPMs exhibited increased expression of known pacemaker ion channels, including Hcn4 and Cx45 as well as upregulation of the mechanosensitive ion channels Piezo1, Trpp2 (PKD2), and TrpM7. Metabolic pathways were broadly downregulated, as were ion channels associated with ventricular excitation-contraction coupling. Tbx18-iPMs also exhibited extensive intracellular cytoskeletal and extracellular matrix remodeling, including 96 differentially expressed proteins associated with the epithelial-to-mesenchymal transition (EMT). RNAseq extended coverage of low abundance transcription factors, revealing upregulation of EMT-inducing Snai1, Snai2, Twist1, Twist2, and Zeb2. Finally, network diffusion mapping of >200 transcriptional regulators indicates EMT and heart development factors occupy adjacent network neighborhoods downstream of Tbx18 but upstream of metabolic control factors. In conclusion, transdifferentiation of cardiac myocytes into pacemaker cells entails massive electrogenic, metabolic, and cytostructural remodeling. Structural changes exhibit hallmarks of the EMT. The results aid ongoing efforts to maximize the yield and phenotypic stability of engineered biological pacemakers.

Using piecewise regression to identify biological phenomena in biotelemetry datasets.

Technological advances in the field of animal tracking have greatly expanded the potential to remotely monitor animals, opening the door to exploring how animals shift their behaviour over time or respond to external stimuli. A wide variety of animal-borne sensors can provide information on an animal's location, movement characteristics, external environmental conditions and internal physiological status. Here, we demonstrate how piecewise regression can be used to identify the presence and timing of potential shifts in a variety of biological responses using multiple biotelemetry data streams. Different biological latent states can be inferred by partitioning a time-series into multiple segments based on changes in modelled responses (e.g. their mean, variance, trend, degree of autocorrelation) and specifying a unique model structure for each interval. We provide six example applications highlighting a variety of taxonomic species, data streams, timescales and biological phenomena. These examples include a short-term behavioural response (flee and return) by a trumpeter swan Cygnus buccinator following a GPS collar deployment; remote identification of parturition based on movements by a pregnant moose Alces alces; a physiological response (spike in heart-rate) in a black bear Ursus americanus to a stressful stimulus (presence of a drone); a mortality event of a trumpeter swan signalled by changes in collar temperature and overall dynamic body acceleration; an unsupervised method for identifying the onset, return, duration and staging use of sandhill crane Antigone canadensis migration; and estimation of the transition between incubation and brood-rearing (i.e. hatching) for a breeding trumpeter swan. We implement analyses using the mcp package in R, which provides functionality for specifying and fitting a wide variety of user-defined model structures in a Bayesian framework and methods for assessing and comparing models using information criteria and cross-validation measures. These simple modelling approaches are accessible to a wide audience and offer a straightforward means of assessing a variety of biologically relevant changes in animal behaviour.

Implementing Biological Pacemakers: Design Criteria for Successful.

Each heartbeat that pumps blood throughout the body is initiated by an electrical impulse generated in the sinoatrial node (SAN). However, a number of disease conditions can hamper the ability of the SAN's pacemaker cells to generate consistent action potentials and maintain an orderly conduction path, leading to arrhythmias. For symptomatic patients, current treatments rely on implantation of an electronic pacing device. However, complications inherent to the indwelling hardware give pause to categorical use of device therapy for a subset of populations, including pediatric patients or those with temporary pacing needs. Cellular-based biological pacemakers, derived in vitro or in situ, could function as a therapeutic alternative to current electronic pacemakers. Understanding how biological pacemakers measure up to the SAN would facilitate defining and demonstrating its advantages over current treatments. In this review, we discuss recent approaches to creating biological pacemakers and delineate design criteria to guide future progress based on insights from basic biology of the SAN. We emphasize the need for long-term efficacy in vivo via maintenance of relevant proteins, source-sink balance, a niche reflective of the native SAN microenvironment, and chronotropic competence. With a focus on such criteria, combined with delivery methods tailored for disease indications, clinical implementation will be attainable.

Improving the accessibility and transferability of machine learning algorithms for identification of animals in camera trap images: MLWIC2.

Motion-activated wildlife cameras (or "camera traps") are frequently used to remotely and noninvasively observe animals. The vast number of images collected from camera trap projects has prompted some biologists to employ machine learning algorithms to automatically recognize species in these images, or at least filter-out images that do not contain animals. These approaches are often limited by model transferability, as a model trained to recognize species from one location might not work as well for the same species in different locations. Furthermore, these methods often require advanced computational skills, making them inaccessible to many biologists. We used 3 million camera trap images from 18 studies in 10 states across the United States of America to train two deep neural networks, one that recognizes 58 species, the "species model," and one that determines if an image is empty or if it contains an animal, the "empty-animal model." Our species model and empty-animal model had accuracies of 96.8% and 97.3%, respectively. Furthermore, the models performed well on some out-of-sample datasets, as the species model had 91% accuracy on species from Canada (accuracy range 36%-91% across all out-of-sample datasets) and the empty-animal model achieved an accuracy of 91%-94% on out-of-sample datasets from different continents. Our software addresses some of the limitations of using machine learning to classify images from camera traps. By including many species from several locations, our species model is potentially applicable to many camera trap studies in North America. We also found that our empty-animal model can facilitate removal of images without animals globally. We provide the trained models in an R package (MLWIC2: Machine Learning for Wildlife Image Classification in R), which contains Shiny Applications that allow scientists with minimal programming experience to use trained models and train new models in six neural network architectures with varying depths.

Novel method for action potential measurements from intact cardiac monolayers with multiwell microelectrode array technology.

The cardiac action potential (AP) is vital for understanding healthy and diseased cardiac biology and drug safety testing. However, techniques for high throughput cardiac AP measurements have been limited. Here, we introduce a novel technique for reliably increasing the coupling of cardiomyocyte syncytium to planar multiwell microelectrode arrays, resulting in a stable, label-free local extracellular action potential (LEAP). We characterized the reliability and stability of LEAP, its relationship to the field potential, and its efficacy for quantifying AP morphology of human induced pluripotent stem cell derived and primary rodent cardiomyocytes. Rise time, action potential duration, beat period, and triangulation were used to quantify compound responses and AP morphology changes induced by genetic modification. LEAP is the first high throughput, non-invasive, label-free, stable method to capture AP morphology from an intact cardiomyocyte syncytium. LEAP can accelerate our understanding of stem cell models, while improving the automation and accuracy of drug testing.

DJ-1 protects the heart against ischemia-reperfusion injury by regulating mitochondrial fission.

Recent data indicates that DJ-1 plays a role in the cellular response to stress. Here, we aimed to examine the underlying molecular mechanisms mediating the actions of DJ-1 in the heart following myocardial ischemia-reperfusion (I/R) injury. In response to I/R injury, DJ-1 KO mice displayed increased areas of infarction and worsened left ventricular function when compared to WT mice, confirming a protective role for DJ-1 in the heart. In an effort to evaluate the potential mechanism(s) responsible for the increased injury in DJ-1 KO mice, we focused on SUMOylation, a post-translational modification process that regulates various aspects of protein function. DJ-1 KO hearts after I/R injury were found to display enhanced accumulation of SUMO-1 modified proteins and reduced SUMO-2/3 modified proteins. Further analysis, revealed that the protein expression of the de-SUMOylation enzyme SENP1 was reduced, whereas the expression of SENP5 was enhanced in DJ-1 KO hearts after I/R injury. Finally, DJ-1 KO hearts were found to display enhanced SUMO-1 modification of dynamin-related protein 1, excessive mitochondrial fission, and dysfunctional mitochondria. Our data demonstrates that the activation of DJ-1 in response to myocardial I/R injury protects the heart by regulating the SUMOylation status of Drp1 and attenuating excessive mitochondrial fission.

In-situ formation of growth-factor-loaded coacervate microparticle-embedded hydrogels for directing encapsulated stem cell fate.

The spontaneous formation of coacervate microdroplet-laden photo-crosslinked hydrogels derived from the simple mixing of oxidized, methacrylated alginate (OMA) and methacrylated gelatin (GelMA) enables simultaneous creation of drug-laden microdroplets and encapsulation of stem cells in photopolymerized coacervate hydrogels under physiological conditions. This can be utilized as a novel platform for in situ formation of localized, sustained bioactive molecule delivery to encapsulate stem cells for therapeutic applications.