Biology subjects

Perry, M. D.

Publications and source records attributed to Perry, M. D..

6 recordsLinked to original sources

bioRxiv2024

A range of voltage-clamp protocol designs for rapid capture of hERG kinetics

We provide details of a series of short voltage-clamp protocols designed for gathering a large amount of information on hERG (Kv11.1) ion channel gating. The protocols have a limited number of steps and consist only of steps and ramps, making them easy to implement on any patch clamp setup, including automated platforms. The primary objective is to assist with parameterisation, selection and refinement of mathematical models of hERG gating. We detail a series of manual and automated model-driven designs, together with an explanation of their rationale and design criteria. Although the protocols are intended to study hERG1a currents, the approaches could be easily extended and generalised to other ion channel currents.

biophysics↗

bioRxiv2023

SARS-CoV-2 lineage assignments using phylogenetic placement/UShER are superior to pangoLEARN machine learning method

With the rapid spread and evolution of SARS-CoV-2, the ability to monitor its transmission and distinguish among viral lineages is critical for pandemic response efforts. The most commonly used software for the lineage assignment of newly isolated SARS-CoV-2 genomes is pangolin, which offers two methods of assignment, pangoLEARN and pUShER. PangoLEARN rapidly assigns lineages using a machine learning algorithm, while pUShER performs a phylogenetic placement to identify the lineage corresponding to a newly sequenced genome. In a preliminary study, we observed that pangoLEARN (decision tree model), while substantially faster than pUShER, offered less consistency across different versions of pangolin v3. Here, we expand upon this analysis to include v3 and v4 of pangolin, which moved the default algorithm for lineage assignment from pangoLEARN in v3 to pUShER in v4, and perform a thorough analysis confirming that pUShER is not only more stable across versions but also more accurate. Our findings suggest that future lineage assignment algorithms for various pathogens should consider the value of phylogenetic placement.

bioinformatics↗

bioRxiv2021

Heterozygous KCNH2 variant phenotyping using Flp-In HEK293 and high-throughput automated patch clamp electrophysiology

KCNH2 is one of the 59 medically actionable genes recommended by the American College of Medical Genetics for reporting of incidental findings from clinical genomic sequencing. However, half of the reported KCNH2 variants in the ClinVar database are classified as variants of uncertain significance. In the absence of strong clinical phenotypes, there is a need for functional phenotyping to help decipher the significance of variants identified incidentally. Here, we report detailed methods for assessing the molecular phenotype of any KCNH2 missense variant. The key components of the assay include quick and cost-effective generation of a bicistronic vector to co-express WT and any KCNH2 variant allele, generation of stable Flp-In HEK293 cell lines and high-throughput automated patch-clamp electrophysiology analysis of channel function. Stable cell lines take 3-4 weeks to produce and can be generated in bulk, which will then allow up to 30 variants to be phenotyped per week after 48 hours of channel expression. This high throughput functional genomics assay will enable a much more rapid assessment of the extent of loss of function of any KCNH2 variant.

biophysics↗

bioRxiv2019

Co-expression of calcium channels and delayed rectifier potassium channels protects the heart from proarrhythmic events

Cardiac electrical activity is controlled by the carefully orchestrated activity of more than a dozen different ion conductances. Yet, there is considerable variability in cardiac ion channel expression levels both within and between subjects. In this study we tested the hypothesis that variations in ion channel expression between individuals are not random but rather there are modules of co-expressed genes and that these modules make electrical signaling in the heart more robust. Meta-analysis of 3653 public RNA-Seq datasets identified a strong correlation between expression of CACNA1C (L-type calcium current, ICaL) and KCNH2 (rapid delayed rectifier K+ current, IKr), which was verified in mRNA extracted from human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CM). In silico modeling, validated with functional measurements in hiPSC-CM, indicates that the co-expression of CACNA1C and KCNH2 limits the variability in action potential duration and reduces susceptibility to early afterdepolarizations, a surrogate marker for pro-arrhythmia. Impact StatementCoexpressed levels of potassium and calcium ion channel genes in the heart encode more robust cardiac electrophysiology and provide insights into genetic basis of arrhythmic risk

biophysics↗

bioRxiv2019

Protocol-dependent differences in IC50 values measured in hERG assays occur in a predictable way and can be used to quantify state preference of drug binding.

Current guidelines around preclinical screening for drug-induced arrhythmias require the measurement of the potency of block of Kv11.1 channels as a surrogate for risk. A shortcoming of this approach is that the measured IC50 of Kv11.1 block varies widely depending on the voltage protocol used in electrophysiological assays. In this study, we aimed to investigate the factors that that contribute to these differences and to identify whether it is possible to make predictions about protocol-dependent block that might facilitate comparison of potencies measured using different assays Our data demonstrate that state preferential binding, together with drug binding kinetics and trapping, is an important determinant of the protocol-dependence of Kv11.1 block. We show for the first time that differences in IC50 measured between protocols occurs in a predictable way, such that machine learning algorithms trained using a selection of simple voltage protocols can indeed predict protocol-dependent potency. Furthermore, we also show that a drugs preference for binding to the open versus the inactivated state of Kv11.1 can also be inferred from differences in IC50 measured between protocols. Our work therefore identifies how state preferential drug binding is a major determinant of the protocol dependence of IC50 measured in preclinical Kv11.1 assays. It also provides a novel method for quantifying the state dependence of Kv11.1 drug binding that will facilitate the development of more complete models of drug binding to Kv11.1 and improve our understanding of proarrhythmic risk associated with compounds that block Kv11.1.

pharmacology and toxicology↗

bioRxiv2017

Pan-cancer study of heterogeneous RNA aberrations

We present the most comprehensive catalogue of cancer-associated gene alterations through characterization of tumor transcriptomes from 1,188 donors of the Pan-Cancer Analysis of Whole Genomes project. Using matched whole-genome sequencing data, we attributed RNA alterations to germline and somatic DNA alterations, revealing likely genetic mechanisms. We identified 444 associations of gene expression with somatic non-coding single-nucleotide variants. We found 1,872 splicing alterations associated with somatic mutation in intronic regions, including novel exonization events associated with Alu elements. Somatic copy number alterations were the major driver of total gene and allele-specific expression (ASE) variation. Additionally, 82% of gene fusions had structural variant support, including 75 of a novel class called \"bridged\" fusions, in which a third genomic location bridged two different genes. Globally, we observe transcriptomic alteration signatures that differ between cancer types and have associations with DNA mutational signatures. Given this unique dataset of RNA alterations, we also identified 1,012 genes significantly altered through both DNA and RNA mechanisms. Our study represents an extensive catalog of RNA alterations and reveals new insights into the heterogeneous molecular mechanisms of cancer gene alterations.

genomics↗