Biology subjects

Bahcheli, A. T.

Publications and source records attributed to Bahcheli, A. T..

10 recordsLinked to original sources

bioRxiv2026

Multi-platform reassessment of human mitochondrial DNA methylation reveals signals consistent with technical artifacts

The existence and functional relevance of mitochondrial DNA methylation remain controversial. Here, we systematically profiled cytosine methylation and hydroxymethylation across human brain and blood tissues spanning healthy and malignant states using orthogonal sequencing approaches that avoid chemical conversion during library preparation. While nuclear DNA exhibited canonical methylation patterns, mitochondrial DNA consistently showed negligible signal, indistinguishable from background technical noise. By mapping cytosine-guanine sites between mitochondrial DNA and nuclear-embedded mitochondrial sequences, we demonstrate the potential of these nuclear counterparts to confound not only cytosine methylation but also hydroxymethylation measurements, corroborating and extending prior findings implicating nuclear contamination as a potential source of apparent mitochondrial epigenetic signals. Additional technical factors that inflate apparent mtDNA methylation signals were identified, including sequence context biases, flow cell chemistries, and coverage-dependent discrepancies between the heavy and light strands. Collectively, these results provide convergent evidence against the presence of biologically meaningful cytosine methylation or hydroxymethylation in mitochondrial DNA. These findings caution against interpreting apparent mtDNA methylation signals in human adult tissues as meaningful without rigorous orthogonal validation and comprehensive consideration of technical and analytical confounding factors.

bioinformatics↗

bioRxiv2026

Chromatin accessibility of primary cancers informs regional mutagenesis in metastases through multi-scale deep learning

Tissue-specific chromatin states shape regional mutation density in primary tumors, but whether this relationship persists in metastases is unclear. We integrated whole-genome sequencing data from 2,507 metastatic tumors across six cancer types with 892 chromatin accessibility and replication timing profiles, and developed CAMM, a multi-scale deep learning model, to jointly predict SNV and indel density across multiple genomic resolutions. The model explained regional variance in mutation density across metastatic cancers and preserved mutagenesis patterns in an independent primary tumor cohort. Chromatin accessibility profiles from tissue-matched primary cancers were informative predictors of regional mutagenesis in metastases, supporting a contribution of lineage-linked chromatin context, as indicated by feature attribution analyses. Genomic windows with mutation burdens exceeding epigenome-based expectations were enriched for known and candidate cancer loci. These results link metastatic regional mutagenesis to tissue-of-origin chromatin accessibility and provide a framework for interpreting mutational processes and prioritizing mutation-enriched loci.

cancer biology↗

bioRxiv2026

Therapy-associated mutagenesis at CTCF binding sites is shaped by chromatin context and DNA repair capacity

Genotoxic cancer therapies introduce DNA damage that can be fixed as somatic mutations in surviving tumor cells. However, the impact of therapy-associated mutagenesis on regulatory elements remains unclear. CTCF binding sites (CBS) are chromatin architectural elements that exhibit recurrent localized mutation enrichment in cancer genomes. We asked whether treatment exposure is associated with increased mutagenesis at CBS in 4,870 whole-genome sequences from metastatic tumors across 17 cancer types and 45 therapies. Radiotherapy and trifluridine exposure in metastatic colorectal cancer were associated with increased mutation enrichment at CBS. This enrichment was pronounced at motif-containing sites and in low-expression or late-replicating genomic contexts. Alterations in DNA damage response genes, including BRCA2, were associated with increased CBS mutation enrichment following radiotherapy. Together, these findings indicate that therapy-associated mutagenesis at CTCF binding sites is shaped by chromatin context and DNA repair capacity, extending the mutational consequences of cancer treatment to regulatory genome architecture.

cancer biology↗

bioRxiv2026

Mutational signatures in cancer genomes alter protein sequence motifs in cellular signaling networks

Somatic mutations in cancer genomes arise from distinct, context-specific mutational processes, yet their functional consequences at the protein and network level remain incompletely understood. Here, we show that mutational processes of single-nucleotide variants (SNVs) can systematically rewire signaling networks by inducing amino acid substitutions in short linear motifs (SLiMs) that mediate interactions with kinases and other signaling proteins. By analysing 11,000 cancer genomes and 144 classes of SLiMs, we identify motif-rewiring SNVs (rwSNVs) that create or disrupt SLiMs or remove phosphorylated residues. Mutational processes of methylcytosine deamination, APOBEC activity, and ultraviolet light exposure emerge as major contributors to motif rewiring. rwSNVs are enriched in cancer driver genes and pathways, linking mutation etiology to functional consequences. rwSNVs at the BRAF V600E hotspot associated with UV-related mutagenesis are predicted to generate a phosphorylation motif recognized by PLK1 kinase. Together, these findings reveal how mutational processes shape oncogenic signaling and tumor heterogeneity.

cancer biology↗

bioRxiv2024

Combinations of genomic alterations and immune microenvironmental features associate with patient survival in multiple cancer types

Oncogenesis and tumor progression are shaped by somatic alterations in the cancer genome and features of the tumor immune microenvironment (TME). How interactions of these two systems influence tumor development and clinical outcomes remains incompletely understood. To address this challenge, we developed the multi-omics analysis framework PACIFIC to systematically integrate genetic cancer drivers and infiltration profiles of immune cells with clinical information. In an analysis of 8500 cancer samples, we report 34 immunogenomic interactions (IGXs) in 13 cancer types in which context-specific combinations of genomic alterations and immune cell activities associate with disease outcomes. Risk associations of IGXs are potentially explained by tumor-intrinsic and microenvironmental metrics of immunogenicity and differential expression of therapeutic targets. In luminal-A breast cancer, MEN1 deletion combined with reduced neutrophils is associated with poor prognosis and deregulation of immune signalling pathways. These findings help elucidate how cancer drivers interact with TME to contribute to tumorigenesis.

cancer biology↗

bioRxiv2023

Directional integration and pathway enrichment analysis for multi-omics data

Omics techniques generate comprehensive profiles of biomolecules in cells and tissues. However, a holistic understanding of the data requires joint multi-omics analyses that are challenging. Here we present DPM, a data fusion method for combining multiple omics datasets using directionality and significance estimates of genes, transcripts, or proteins. DPM allows users to define how the input datasets are expected to interact directionally, reflecting the initial experimental design or regulatory relationships between the datasets. DPM statistically prioritises genes and pathways that change consistently across the datasets, while penalising those violating the constraints. Joint analyses of transcriptomic, proteomic, DNA methylation, and clinical datasets of cancer samples demonstrate how directional integration identifies genes and pathways modulated across omics datasets, highlights those with inconsistent evidence, and reveals candidate biomarkers with prognostic signals in multiple datasets. DPM is implemented in the ActivePathways method and provides a general framework for testing detailed hypotheses in multi-omics data.

bioinformatics↗

bioRxiv2023

Pan-cancer analysis of the ion permeome reveals functional regulators of glioblastoma aggression

Ion channels, transporters, and other ion-permeating proteins, collectively comprising the ion permeome (IP), are common drug targets. However, their roles in cancer are understudied. Our integrative pan-cancer analysis shows that IP genes display highly-elevated expression patterns in subsets of cancer samples significantly more often than expected transcriptome-wide. To enable target identification, we identified 410 survival-associated IP genes in 29 cancer types using a machine learning approach. Notably, GJB2 and SCN9A show prominent expression in neoplastic cells and associate with poor prognosis in glioblastoma (GBM), the most common and aggressive brain cancer. GJB2 or SCN9A knockdown in patient-derived GBM cells induces transcriptome-wide changes involving neural projection and proliferation pathways, impairs cell viability and tumor sphere formation, mitigates tunneling nanotube formation, and extends the survival of GBM-bearing mice. Thus, aberrant activation of IP genes appears as a pan-cancer feature of tumor heterogeneity that can be exploited for mechanistic insights and therapy development.

cancer biology↗

bioRxiv2023

Mutational processes of tobacco smoking and APOBEC activity generate protein-truncating mutations in cancer genomes

Mutational signatures represent a footprint of tumor evolution and its endogenous and exogenous mutational processes. However, their functional impact on the proteome remains incompletely understood. We analysed the protein-coding impact of single base substitution signatures in 12,341 cancer genomes from 18 cancer types. Stop-gain mutations (SGMs) were strongly enriched in the signatures of tobacco smoking, APOBEC cytidine deaminases, and reactive oxygen species. These mutational processes affect specific trinucleotide contexts to substitute serine and glutamic acid residues with stop codons. SGMs are enriched in cancer hallmark pathways and tumor suppressors such as TP53, FAT1, and APC. Tobacco-driven SGMs in lung cancer correlate with lifetime smoking history and highlight a preventable determinant of these harmful mutations. Our study exposes SGM expansion as a genetic mechanism by which endogenous and carcinogenic mutational processes contribute to protein loss-of-function, oncogenesis, and tumor heterogeneity, providing potential translational and mechanistic insights.

cancer biology↗

bioRxiv2021

Telomere-to-telomere genome assembly of Phaeodactylum tricornutum

Phaeodactylum tricornutum is a marine diatom with a growing genetic toolbox available and is being used in many synthetic biology applications. While most of the genome has been assembled, the currently available genome assembly is not a completed telomere-to-telomere assembly. Here, we used Oxford Nanopore long reads to build a telomere-to-telomere genome for Phaeodactylum tricornutum. We developed a graph-based approach to extract all unique telomeres, and used this information to manually correct assembly errors. In total, we found 25 nuclear chromosomes that comprise all previously assembled fragments, in addition to the chloroplast and mitochondrial genomes. We found that chromosome 19 has filtered long-read coverage and a quality estimate that suggests significantly less haplotype sequence variation than the other chromosomes. This work improves upon the previous genome assembly and provides new opportunities for genetic engineering of this species, including creating designer synthetic chromosomes.

genomics↗

bioRxiv2020

Complete and validated genomes from a metagenome

0.1The assembly and binning of metagenomically-assembled genomes (MAGs) using Illumina sequencing has improved the genomic characterization of unculturable communities. However, short-read-only metagenomic assemblies rarely result in completed genomes because of the difficulty assembling repetitive regions. Here, we present a strategy to complete and validate multiple MAGs from a bacterial community using a combination of short and ultra long reads (N50 > 25 kb). Our strategy is to perform an initial long read-only metagenomic assembly using metaFlye, followed by multiple rounds of polishing using both long and short reads. To validate the genomes, we verified that longs reads spanned the regions that were not supported by uniquely mapped paired-end Illumina sequences. We obtained multiple complete genomes from a naphthenic acid-degrading community, including one from the recently proposed Candidate Phyla Radiation. The majority of the population is represented by the assembled genomes; recruiting 63.77 % of Nanopore reads, and 64.38 % of Illumina reads. The pipeline we developed will enable researchers to validate genomes from metagenomic assemblies, increasing the quality of metagenomically assembled genomes through additional scrutiny.

bioinformatics↗