Biology subjects

Maertens, G. N.

Publications and source records attributed to Maertens, G. N..

4 recordsLinked to original sources

bioRxiv2026

inteRelate: flexible and thorough relating of genomic interval datasets through comparative overlap analysis

Summary Testing spatial relationships between genome-mapped features is both a common source of hypothesis generation and an additional layer of supporting evidence for experimental findings. Many computational tools automate the statistical association procedures used to assess overlap between pairs of genomic features. However, none provides a dedicated workflow that directly compares multiple features by assessing their overlap with a separate, common feature, first testing for overall heterogeneity and then identifying which overlap rates differ. Such comparative overlap analysis could directly facilitate comparisons of features within the same class across disease states, cell types, experimental perturbations, and other biological contexts. Here, we describe inteRelate, a software package that uses genomic interval datasets to test spatial relationships between genome-mapped features through comparative overlap analysis. The package functions as an end-to-end pipeline that is highly tunable and thorough in its statistical association procedures. We use experimental data to demonstrate the automation, accuracy, and insight inteRelate provides. Availability and implementation inteRelate is available at https://github.com/loggy01/interelate and archived at https://zenodo.org/records/21891072. Example uses are available in the online supplement. Additionally, the example datasets and results are available at https://zenodo.org/records/22012767.

genomics↗

bioRxiv2026

HTLV-1 intasome recruits the PP2A-B56 holoenzyme and restricts its phosphatase activity

Integrase catalyses the insertion of a DNA copy of the retroviral genome into host cell chromatin. Human T-cell lymphotropic virus type 1 (HTLV-1) and other deltaretroviral integrases associate with protein phosphatase 2A holoenzymes containing B56 regulatory subunits (PP2A-B56). Here, we show that integrase mutants defective in binding to most B56 isoforms retain intrinsic DNA strand transfer activity but are impaired in establishing infection. Using single-particle cryo-EM, we determined the structure of the simian T-cell lymphotropic virus type 1 (STLV-1) intasome in a 0.5-MDa complex with two copies of the heterotrimeric PP2A-B56{gamma} holoenzyme at 2.8 [A] resolution. The structure reveals that, in addition to engaging B56, integrase forms direct contacts with the catalytic subunit of PP2A and sterically occludes the phosphatase active site, preventing substrate access. Consistent with these findings, we show that the HTLV-1 intasome suppresses PP2A catalytic activity in a manner dependent on the integrase LxxIxE short linear motif. We further demonstrate that pharmacological inhibition of PP2A does not impair HTLV-1 infection. Together, our results indicate that recruitment of PP2A-B56 by the intasome serves a structural rather than catalytic function.

microbiology↗

bioRxiv2024

AlphaRING: Missense Variant Classification via Protein Modelling and Residue Interaction Network Analysis

BackgroundAccurate interpretation of missense variants remains a significant challenge hindering genomic diagnosis. While state-of-the-art machine learning and deep learning predictors offer high accuracy, they often lack the transparency required for clinical evidence weighting. To bridge this gap between accuracy and clinical utility, we developed AlphaRING-X. MethodsAlphaRING-X is an open-source framework that integrates local and global protein structural stability features using an efficient implementation of gradient boosting, XGBoost, to predict variant deleteriousness. Local stability is interrogated through a combination of AlphaFold-based modelling and residue interaction network analysis. Changes in global stability upon mutation ({Delta}{Delta}G) are estimated using FoldX. For each prediction, AlphaRING-X quantifies the magnitude and direction of each features contribution using Shapley additive explanations (SHAP), providing a unified yet interpretable score. We trained and evaluated the model using a gold standard ClinVar dataset of validated neutral and deleterious variants. ResultsAlphaRING-X achieved an area under the receiver operator curve of 0.94, significantly outperforming widely used predictors such as CADD. Crucially, it provided unambiguous classification for 95.5% of variants at 90% precision in both neutral and deleterious classes. We analysed each predictions SHAP values, identifying local connectivity and disorder as the strongest contributors. ConclusionsAlphaRING-X combines high-performance prediction with the interpretability necessary for clinical decision-making. Its flexible, open-source architecture makes it a powerful, transparent tool for enhancing genomic diagnostics and advancing precision medicine.

bioinformatics↗

bioRxiv2020

CRYO-EM STRUCTURE OF THE DELTA-RETROVIRAL INTASOME IN COMPLEX WITH THE PP2A REGULATORY SUBUNIT B56gamma

The Retroviridae delta-retrovirus genus includes the most oncogenic pathogen- human T-cell lymphotropic virus type 1 (HTLV-1)(1). Many of the ~20 million people infected with HTLV-1 will develop severe leukaemia (2) or an ALS-like motor disease (3) unless a therapy becomes available. A key step in the establishment of infection is the integration of viral genetic material into the host genome, catalysed by the viral integrase (IN) enzyme. Here we used X-ray crystallography and single-particle cryo-electron microscopy to determine the structure of functional delta-retroviral IN assembled on viral DNA ends and bound the B56{gamma} subunit of its human host factor, the protein phosphatase 2A (4). The structure reveals a tetrameric IN assembly bound to the phosphatase via a conserved short linear motif found within the extended linker connecting the catalytic core (CCD) and C-terminal (CTD) IN domains. Unexpectedly, all four IN subunits are involved in B56{gamma} binding, taking advantage of the flexibility of the CCD-CTD linkers. Our results fill the current gap in the structural understanding of the delta-retroviral integration machinery. Insight into the interactions between the delta-retroviral intasome and the host will be crucial for understanding the pattern of integration events in infected individuals and therefore bears important clinical implications.

biochemistry↗