Biology subjects

Rubin, J. D.

Publications and source records attributed to Rubin, J. D..

8 recordsLinked to original sources

bioRxiv2025

Induced Proteinuria Enhances Adeno-Associated Virus Transduction of Renal Tubule Epithelial Cells After Intravenous Administration

A variety of genetic diseases of the kidney tubule are amenable to correction via gene therapy. However, gene delivery to renal tubule epithelial cells mediated by viral vectors via the blood is inefficient due to the permselectivity of the glomerular barrier. We hypothesized that effacement of podocyte foot processes would disrupt typical glomerular limitations on filtration and make renal tubule epithelial cells susceptible to transduction from viral vectors delivered intravenously. We determined that adeno-associated virus serotype 8 (AAV8) transduced significantly more epithelial cells in the kidney under the conditions of LPS-induced proteinuria. Use of AAV1 in tandem with LPS-induced proteinuria yielded an ideal two-pronged effect of both partially detargeting the liver and transducing the kidney with a higher bioluminescent signal than AAV8 did, and at half of the dose. Using adenovirus serotype 5 (Ad5) in conjunction with LPS-induced proteinuria showed that kidney transduction was enhanced, but only in glomerular cells. These studies mechanistically test the efficacy of different viral vectors and demonstrate their capacity to transduce kidney epithelial cells. This is a fundamental step in designing future treatments for kidney gene therapy. Significance StatementThe slit diaphragms in the glomerulus of the kidney are too narrow to allow most solute from the blood to enter the nephron. As a result, large particles such as viral vectors generally cannot access tubule epithelial cells necessary to correct genetic disorders. In this study, mice are induced into a state of proteinuria and subsequently administered viral vectors intravenously. This group of mice had higher levels of transduced kidney epithelial cells than the control (non-proteinuria) group. The induction of transient proteinuria before intravenous viral vector administration is a novel approach that could make tubulopathies treatable via gene therapy in both animal models and humans.

genetics↗

bioRxiv2024

SAFARI: Pangenome Alignment of Ancient DNA Using Purine/Pyrimidine Encodings

Aligning DNA sequences retrieved from fossils or other paleontological artifacts, referred to as ancient DNA, is particularly challenging due to the short sequence length and chemical damage which creates a specific pattern of substitution (C[->]T and G[->]A) in addition to the heightened divergence between the sample and the reference genome thus exacerbating reference bias. This bias can be mitigated by aligning to pangenome graphs to incorporate documented organismic variation, but this approach still suffers from substitution patterns due to chemical damage. We introduce a novel methodology introducing the RYmer index, a variant of the commonly-used minimizer index which represents purines (A,G) and pyrimidines (C,T) as R and Y respectively. This creates an indexing scheme robust to the aforementioned chemical damage. We implemented SAFARI, an ancient DNA damage-aware version of the pangenome aligner vg giraffe which uses RYmers to rescue alignments containing deaminated seeds. We show that our approach produces more correct alignments from ancient DNA sequences than current approaches while maintaining a tolerable rate of spurious alignments. In addition, we demonstrate that our algorithm improves the estimate of the rate of ancient DNA damage, especially for highly damaged samples. Crucially, we show that this improved alignment can directly translate into better insights gained from the data by showcasing its integration with a number of extant pangenome tools.

bioinformatics↗

bioRxiv2024

soibean: High-resolution Taxonomic Identification of Ancient Environmental DNA Using Mitochondrial Pangenome Graphs

Ancient environmental DNA (aeDNA) is becoming a powerful tool to gain insights about past ecosystems. However, several methodological challenges remain, particularly for classifying the DNA to species level and conducting phylogenetic placement. Current methods, primarily tailored for modern datasets, fail to capture several idiosyncrasies of aeDNA, including species mixtures from closely related species and ancestral divergence. We introduce soibean, a novel tool that utilises pangenomic graphs for identifying species from ancient environmental mitochondrial reads. It outperforms existing methods in accurately identifying species from multiple sources within a sample, enhancing phylogenetic analysis for aeDNA. soibean employs a damage-aware likelihood model for precise identification at low-coverage with high damage rate, demonstrating effectiveness through simulated data tests and empirical validation. Notably, our method uncovered new empirical results in published datasets, including using porpoise whales as food in a Mesolithic community in Sweden, demonstrating its potential to reveal previously unrecognised findings in aeDNA studies.

bioinformatics↗

bioRxiv2023

The Limits of Haplotype-Based Approaches: Exploring the Applicability of the Li and Stephens Haplotype-Copying Model to Ancient Samples

The Li and Stephens (LS) haplotype-copying model is a seminal framework that represents a target haplotype as an imperfect mosaic of a set of reference haplotypes. Using a hidden Markov model, it can switch from different source haplotypes to model recombinations. This model has been used in several applications in modern populations including phasing and inference of ancestry. However, recent publications have looked at the applicability of the model to using ancient individuals as targets and modern reference panels as source data. Previous research exploring the impact of time separation between the modern references and the ancient target on the models behavior relied on coalescent simulation to generate genetic variation data, which could lead to an underestimation of the ancient populations genetic diversity. Further, these simulations were restricted to a relatively short time period of anatomically modern human history. To overcome these limitations, our study evaluates the robustness of the LS model using forward-simulated data enabling us to sample haplotypes that do not have direct descendants among the modern population. Additionally, we evaluate the model under the simple demographic scenario of a constant-sized continuous population starting 1.5M years ago to isolate the effect of time separation. Results indicate good performance for target haplotypes up to 900,000 years old, suggesting potential applicability to ancient DNA (aDNA) from anatomically modern humans. Although more complex demographic scenarios should be considered for a definitive answer, this research serves as a starting point for evaluating the haplotype-copying framework in aDNA data analysis.

genomics↗

bioRxiv2023

euka: Robust detection of eukaryotic taxa from modern and ancient environmental DNA using pangenomic reference graphs.

1. Ancient environmental DNA (eDNA) is a crucial source of in-formation for past environmental reconstruction. However, the com-putational analysis of ancient eDNA involves not only the inherited challenges of ancient DNA (aDNA) but also the typical difficulties of eDNA samples, such as taxonomic identification and abundance esti-mation of identified taxonomic groups. Current methods for ancient eDNA fall into those that only perform mapping followed by taxo-nomic identification and those that purport to do abundance estima-tion. The former leaves abundance estimates to users, while methods for the latter are not designed for large metagenomic datasets and are often imprecise and challenging to use. 2. Here, we introduce euka, a tool designed for rapid and accurate characterisation of ancient eDNA samples. We use a taxonomy-based pangenome graph of reference genomes for robustly assigning DNA sequences and use a maximum-likelihood framework for abundance estimation. At the present time, our database is restricted to mito-chondrial genomes of tetrapods and arthropods but can be expanded in future versions. 3. We find euka to outperform current taxonomic profiling tools as well as their abundance estimates. Crucially, we show that regardless of the filtering threshold set by existing methods, euka demonstrates higher accuracy. Furthermore, our approach is robust to sparse data, which is idiosyncratic of ancient eDNA, detecting a taxon with an average of fifty reads aligning. We also show that euka is consistent with competing tools on empirical samples and about ten times faster than current quantification tools. 4. eukas features are fine-tuned to deal with the challenges of ancient eDNA, making it a simple-to-use, all-in-one tool. It is available on GitHub: https://github.com/grenaud/vgan. euka enables re-searchers to quickly assess and characterise their sample, thus allowing it to be used as a routine screening tool for ancient eDNA.

bioinformatics↗

bioRxiv2022

HaploCart: Human mtDNA Haplogroup Classification Using a Pangenomic Reference Graph

Current mitochondrial DNA (mtDNA) haplogroup classification tools map reads to a single reference genome and perform inference based on the detected mutations to this reference. This approach biases haplogroup assignments towards the reference and prohibits accurate calculations of the uncertainty in assignment. We present HaploCart, an mtDNA haplogroup classifier which uses VGs pangenomic reference graph framework together with principles of Bayesian inference. We demonstrate that our approach significantly outperforms available tools by being more robust to lower coverage or incomplete consensus sequences and producing phylogenetically-aware confidence scores that are unbiased towards any haplogroup. HaploCart is available both as a command-line tool and through a user-friendly web interface. The program written in C++ accepts as input consensus FASTA, FASTQ, or GAM files, and outputs a text file with the haplogroup assignments along with confidence estimates. Our work considerably reduces the amount of data required to obtain a confident mitochondrial haplogroup assignment. HaploCart is available as a command-line tool at https://github.com/grenaud/vgan and as a web server at https://services.healthtech.dtu.dk/service. php?HaploCart.

bioinformatics↗

bioRxiv2020

Transcription factor enrichment analysis (TFEA): Quantifying the activity of hundreds of transcription factors from a single experiment

1Detecting differential activation of transcription factors (TFs) in response to perturbation provides insight into cellular processes. Transcription Factor Enrichment Analysis (TFEA) is a robust and reliable computational method that detects differential activity of hundreds of TFs given any set of perturbation data. TFEA draws inspiration from GSEA and detects positional motif enrichment within a list of ranked regions of interest (ROIs). As ROIs are typically inferred from the data, we also introduce muMerge, a statistically principled method of generating a consensus list of ROIs from multiple replicates and conditions. TFEA is broadly applicable to data that informs on transcriptional regulation including nascent (eg. PRO-Seq), CAGE, ChIP-Seq, and accessibility (e.g. ATAC-Seq). TFEA not only identifies the key regulators responding to a perturbation, but also temporally unravels regulatory networks with time series data. Consequently, TFEA serves as a hypothesis-generating tool that provides an easy, rigorous, and cost-effective means to broadly assess TF activity yielding new biological insights.

bioinformatics↗

bioRxiv2019

Suppression of p53 response by targeting p53-Mediator binding with a stapled peptide

DNA-binding transcription factors (TFs) remain challenging to target with molecular probes. Many TFs function in part through interaction with Mediator; we sought to block p53 function by disrupting the p53-Mediator interaction. Through rational design and activity-based screening, we characterized a stapled peptide, with functional mimics of both p53 activation domains, that selectively inhibited p53- and Mediator-dependent transcription in vitro. This \"bivalent peptide\" also suppressed p53 transcriptional response in human cancer cells. Our strategy circumvents the TF and instead targets the TF-Mediator interface, with desired transcriptional outcomes. Different TFs target Mediator through different subunits, suggesting this strategy could be broadly applied.

molecular biology↗