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Biology subjects

Toth-Petroczy, A.

Publications and source records attributed to Toth-Petroczy, A..

2 recordsLinked to original sources

Homozygous TRPV4 loss-of-function mutation causes a severe form of distal Hereditary Motor Neuropathy (dHMN)

ObjectiveThe objective of this study is to identify the genetic cause of disease in a congenital form of congenital spinal muscular atrophy and arthrogryposis (CSMAA).\n\nMethodsA 2-year-old boy was diagnosed with arthrogryposis multiplex congenita, severe skeletal abnormalities, torticollis, vocal cord paralysis and diminished lower limb movement. Whole exome sequencing was performed on the proband and family members. In silico modeling of protein structure and heterologous protein expression and cytotoxicity assays were performed to validate pathogenicity of the identified variant.\n\nResultsWhole exome sequencing revealed a homozygous mutation in the TRPV4 gene (c.281C>T; p.S94L). The identification of a recessive mutation in TRPV4 extends the spectrum of mutations in recessive forms of the TRPV4-associated disease. p.S94L and other previously identified TRPV4 variants in different protein domains were compared in structural modeling and functional studies. In silico structural modeling suggests that the p.S94L mutation is in the disordered N-terminal region proximal to important regulatory binding sites for phosphoinositides and for PACSIN3, which could lead to alterations in trafficking and/or channel sensitivity. Functional studies by western blot and immunohistochemical analysis show that p.S94L reduces TRPV4 protein stability because of increased cytotoxicity and therefore involves a gain-of-function mechanism.\n\nConclusionThis study identifies a novel homozygous mutation in TRPV4 as a cause of the recessive form of congenital spinal muscular atrophy and arthrogryposis.

genetics

The EVcouplings Python framework for coevolutionary sequence analysis

SummaryCoevolutionary sequence analysis has become a commonly used technique for de novo prediction of the structure and function of proteins, RNA, and protein complexes. This approach requires extensive computational pipelines that integrate multiple tools, databases, and data processing steps. We present the EVcouplings framework, a fully integrated open-source application and Python package for coevolutionary analysis. The framework enables generation of sequence alignments, calculation and evaluation of evolutionary couplings (ECs), and de novo prediction of structure and mutation effects. The application has an easy to use command line interface to run workflows with user control over all analysis parameters, while the underlying modular Python package allows interactive data analysis and rapid development of new workflows. Through this multi-layered approach, the EVcouplings framework makes the full power of coevolutionary analyses available to entry-level and advanced users.\n\nAvailabilityhttps://github.com/debbiemarkslab/evcouplings\n\nContactsander.research@gmail.com, debbie@hms.harvard.edu

bioinformatics