18 research outputs found
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Calcium, TRPC channels, and regulation of the actin cytoskeleton in podocytes: towards a future of targeted therapies
With more than 6,000 new pediatric patients with treatment-resistant nephrotic syndrome in the US each year alone, the unmet need for novel, podocyte-specific therapies is substantial. Recently, the established therapeutic benefit of angiotensin-converting enzyme (ACE) inhibitors and angiotensin receptor blockers (ARB) was used as a starting point to gain insight into the pathomechanism of primary podocytopathies. A calcium (Ca2+)-mediated pathway has been identified that connects the angiotensin type 1 receptor (AT1R) to podocyte cytoskeletal dynamics, essential for a functioning glomerular filtration barrier. This discovery provided an important missing piece in our understanding of the pathomechanism of filter barrier damage, revealing Ca2+ signaling as critical for podocyte health and disease. The identification of the two Ca2+ permeant channels TRPC5 and TRPC6 as mediators of this pathway not only bolstered the importance of podocyte cytoskeleton dynamics but also revealed promising drug targets for treatment-resistant nephrotic syndrome. This review will focus on this novel signaling pathway in primary podocytopathies and its implications for next-generation therapies for glomerular disease
Exact and Approximate Stochastic Simulation of Intracellular Calcium Dynamics
In simulations of chemical systems, the main task is to find an exact or approximate solution of the chemical master equation (CME) that satisfies certain constraints with respect to computation time and accuracy. While Brownian motion simulations of single molecules are often too time consuming to represent the mesoscopic level, the classical Gillespie algorithm is a stochastically exact algorithm that provides satisfying results in the representation of calcium microdomains. Gillespie's algorithm can be approximated via
the tau-leap method and the chemical Langevin equation (CLE). Both methods lead to a substantial acceleration in computation time and a relatively small decrease in accuracy. Elimination of the noise terms leads to the classical, deterministic reaction rate equations (RRE). For complex multiscale systems, hybrid simulations are increasingly
proposed to combine the advantages of stochastic and deterministic algorithms. An often used exemplary cell type in this context are striated muscle cells (e.g., cardiac and skeletal muscle cells).
The properties of these cells are well described and they express many common calcium-dependent signaling
pathways. The purpose of the present paper is to provide an overview of the aforementioned simulation approaches and their mutual relationships in the spectrum ranging from stochastic to deterministic algorithms
High-throughput calculations of magnetic topological materials
The discoveries of intrinsically magnetic topological materials, including
semimetals with a large anomalous Hall effect and axion insulators, have
directed fundamental research in solid-state materials. Topological quantum
chemistry has enabled the understanding of and the search for paramagnetic
topological materials. Using magnetic topological indices obtained from
magnetic topological quantum chemistry (MTQC), here we perform a
high-throughput search for magnetic topological materials based on
first-principles calculations. We use as our starting point the Magnetic
Materials Database on the Bilbao Crystallographic Server, which contains more
than 549 magnetic compounds with magnetic structures deduced from
neutron-scattering experiments, and identify 130 enforced semimetals (for which
the band crossings are implied by symmetry eigenvalues), and topological
insulators. For each compound, we perform complete electronic structure
calculations, which include complete topological phase diagrams using different
values of the Hubbard potential. Using a custom code to find the magnetic
co-representations of all bands in all magnetic space groups, we generate data
to be fed into the algorithm of MTQC to determine the topology of each magnetic
material. Several of these materials display previously unknown topological
phases, including symmetry-indicated magnetic semimetals, three-dimensional
anomalous Hall insulators and higher-order magnetic semimetals. We analyse
topological trends in the materials under varying interactions: 60 per cent of
the 130 topological materials have topologies sensitive to interactions, and
the others have stable topologies under varying interactions. We provide a
materials database for future experimental studies and open-source code for
diagnosing topologies of magnetic materials.Comment: 228 pages; Full topologies and band structures are provided on the
Topological Magnetic Materials Database
https://www.topologicalquantumchemistry.fr/magnetic
A small-molecule inhibitor of TRPC5 ion channels suppresses progressive kidney disease in animal models
Progressive kidney diseases are often associated with scarring of the kidney’s filtration unit, a condition called focal segmental glomerulosclerosis (FSGS). This scarring is due to loss of podocytes, cells critical for glomerular filtration, and leads to proteinuria and kidney failure. Inherited forms of FSGS are caused by Rac1-activating mutations, and Rac1 induces TRPC5 ion channel activity and cytoskeletal remodeling in podocytes. Whether TRPC5 activity mediates FSGS onset and progression is unknown. We identified a small molecule, AC1903, that specifically blocks TRPC5 channel activity in glomeruli of proteinuric rats. Chronic administration of AC1903 suppressed severe proteinuria and prevented podocyte loss in a transgenic rat model of FSGS. AC1903 also provided therapeutic benefit in a rat model of hypertensive proteinuric kidney disease. These data indicate that TRPC5 activity drives disease and that TRPC5 inhibitors may be valuable for the treatment of progressive kidney diseases.National Institutes of Health (U.S.) (Grant DK095045)National Institutes of Health (U.S.) (Grant DK099465)National Institutes of Health (U.S.) (Grant DK103658)National Institutes of Health (U.S.) (Grant DK083511)National Institutes of Health (U.S.) (Grant DK093746
Prediction of the intestinal resistome by a three-dimensional structure-based method
The intestinal microbiota is considered to be a major reservoir of antibiotic resistance determinants (ARDs) that could potentially be transferred to bacterial pathogens via mobile genetic elements. Yet, this assumption is poorly supported by empirical evidence due to the distant homologies between known ARDs (mostly from culturable bacteria) and ARDs from the intestinal microbiota. Consequently, an accurate census of intestinal ARDs (that is, the intestinal resistome) has not yet been fully determined. For this purpose, we developed and validated an annotation method (called pairwise comparative modelling) on the basis of a three-dimensional structure (homology comparative modelling), leading to the prediction of 6,095 ARDs in a catalogue of 3.9 million proteins from the human intestinal microbiota. We found that the majority of predicted ARDs (pdARDs) were distantly related to known ARDs (mean amino acid identity 29.8%) and found little evidence supporting their transfer between species. According to the composition of their resistome, we were able to cluster subjects from the MetaHIT cohort (n = 663) into six resistotypes that were connected to the previously described enterotypes. Finally, we found that the relative abundance of pdARDs was positively associated with gene richness, but not when subjects were exposed to antibiotics. Altogether, our results indicate that the majority of intestinal microbiota ARDs can be considered intrinsic to the dominant commensal microbiota and that these genes are rarely shared with bacterial pathogens
Topological materials discovery from crystal symmetry
Topological materials discovery has evolved at a rapid pace over the past 15 years following the identification of the first nonmagnetic topological insulators (TIs), topological crystalline insulators (TCIs) and 3D topological semimetals (TSMs). Most recently, through complete analyses of symmetry-allowed band structures — including the theory of topological quantum chemistry (TQC) — researchers have determined crystal-symmetry-enhanced Wilson-loop and complete symmetry-based indicators for nonmagnetic topological phases, leading to the discovery of higher-order TCIs and TSMs. The recent application of TQC and related methods to high-throughput materials discovery has revealed that over half of the known stoichiometric, solid-state, nonmagnetic materials are topological at the Fermi level, over 85 per cent of the known stoichiometric materials host energetically isolated topological bands, and just under two-thirds of the energetically isolated bands in known materials carry the stable topology of a TI or TCI. In this Review, we survey topological electronic materials discovery in nonmagnetic crystalline solids from the prediction of the first 2D and 3D TIs to the recently introduced methods that have facilitated large-scale searches for topological materials. We also discuss future venues for the identification and manipulation of solid-state topological phases, including charge-density-wave compounds, magnetic materials, and 2D few-layer devices