Grein, S. | bioRxiv Science

bioRxiv2022

Secreted long non-coding RNAs Gadlor1 and Gadlor2 affect multiple cardiac cell types and aggravate cardiac remodeling during pressure overload

BackgroundPathological overload triggers maladaptive myocardial remodeling that leads to heart failure. Recent studies have shown that long non-coding RNAs (lncRNAs) regulate cardiac remodeling. This study investigates two recently discovered, secreted lncRNAs, Gadlor1 and Gadlor2 (Gadlor 1/2). MethodsWe generated compound Gadlor1/2 knock-out (KO) mice and compared their response to pressure overload by transverse aortic constriction (TAC) to that of wild-type (WT) littermates. Endothelial cells, fibroblasts and cardiomyocytes were isolated from the hearts of both genotypes after TAC and their transcriptome was investigated by RNA sequencing. Gadlor target proteins were identified by RNA antisense purification coupled with mass spectrometry (RAP-MS) in cardiomyocytes. In addition, we investigated the effects of cardiac overexpression of Gadlor1/2. ResultsGadlor1/2 are jointly upregulated in failing mouse hearts as well as in the myocardium of heart failure patients. Cardiac overexpression of Gadlor1 and Gadlor2 aggravated myocardial dysfunction and enhanced hypertrophic and fibrotic remodeling in mice exposed to pressure overload. Compound Gadlor1/2 KO mice, in turn, exerted markedly reduced myocardial hypertrophy, fibrosis and dysfunction, but more angiogenesis during short and long-standing pressure overload. Paradoxically, Gadlor1/2 KO mice suffered from sudden death during prolonged overload, possibly due to cardiac arrhythmia. Gadlor1 and Gadlor2, which are mainly expressed in endothelial cells (ECs) in the heart, where they inhibit pro-angiogenic gene-expression, are strongly secreted within extracellular vesicles (EVs). These EVs transfer Gadlor lncRNAs to cardiomyocytes, where they bind and activate calmodulin-dependent kinase II, induce pro-hypertrophic gene-expression and enhance calcium re-uptake into the sarcoplasmic reticulum. ConclusionGadlor1 and Gadlor2 are lncRNAs that are mainly enriched in EC-derived EVs and are jointly upregulated in mouse and human hearts during pathological overload. We reveal a crucial endothelial cell-cardiomyocyte crosstalk, which aims at restoring calcium homeostasis in cardiomyocytes during overload at the cost of aggravated hypertrophy and fibrosis.

systems biology↗

bioRxiv2022

Efficient computation of adjoint sensitivities at steady-state in ODE models of biochemical reaction networks

Dynamical models in the form of systems of ordinary differential equations have become a standard tool in systems biology. Many parameters of such models are usually unknown and have to be inferred from experimental data. Gradient-based optimization has proven to be effective for parameter estimation. However, computing gradients becomes increasingly costly for larger models, which are required for capturing the complex interactions of multiple biochemical pathways. Adjoint sensitivity analysis has been pivotal for working with such large models, but methods tailored for steady-state data are currently not available. We propose a new adjoint method for computing gradients, which is applicable if the experimental data include steady-state measurements. The method is based on a reformulation of the backward integration problem to a system of linear algebraic equations. The evaluation of the proposed method using real-world problems shows a speedup of total simulation time by a factor of up to 4.4. Our results demonstrate that the proposed approach can achieve a substantial improvement in computation time, in particular for large-scale models, where computational efficiency is critical. Author summaryLarge-scale dynamical models are nowadays widely used for the analysis of complex processes and the integration of large-scale data sets. However, computational cost is often a bottleneck. Here, we propose a new gradient computation method that facilitates the parameterization of large-scale models based on steady-state measurements. The method can be combined with existing gradient computation methods for time-course measurements. Accordingly, it is an essential contribution to the environment of computationally efficient approaches for the study of large-scale screening and omics data, but not tailored to biological applications, and, therefore, also useful beyond the field of computational biology.

systems biology↗