Biology subjects

Oikonomou, A.

Publications and source records attributed to Oikonomou, A..

9 recordsLinked to original sources

bioRxiv2026

A Generalised Epigenetic Clock Reveals Therapeutic Vulnerabilities Linked to Ageing in Cancer Cells

Epigenetic clocks estimate biological age from DNA methylation patterns but perform poorly in cancer due to extensive epigenetic reprogramming, limiting the study of ageing in tumour biology. Here, we develop GepiClock, an epigenetic clock trained on DNA methylation data from 32 cancer types in The Cancer Genome Atlas. Based on 4,862 CpG sites, GepiClock accurately predicts age across both tumour and normal samples, indicating that core ageing-associated methylation programmes remain detectable despite malignant transformation. Applying GepiClock to molecularly profiled cancer cell lines with matched drug response and CRISPR screening data revealed age-associated vulnerabilities. Younger-predicted cell lines were more sensitive to mTOR, MEK1/2 and HSP90 inhibitors, whereas older lines showed increased sensitivity to AKT and PI3K inhibitors. Additional cancer-type-specific patterns and age-associated genetic dependencies were identified. These findings establish a framework to quantify biological age in cancer and link ageing-associated states to therapeutic vulnerabilities.

bioinformatics↗

bioRxiv2026

BioBrain: A Multi-Agent Framework for Natural Language Driven Quantitative Microscopy Data Analysis

Advances in fluorescence microscopy have dramatically expanded the range of biological questions that can be addressed, enabling quantitative observations of molecular interactions and cellular dynamics with unprecedented spatial and temporal resolution. However, the growing complexity of imaging data has outpaced our ability to analyze them. Despite numerous computational methods exist, they often rely on specialized software environments, heterogeneous data formats, and technical expertise, limiting adoption and widening the gap between data acquisition and quantitative biological interpretation. Here we introduce BioBrain, a multi-agent framework that translates natural-language analytical goals into executable and reproducible microscopy analysis pipelines. Instead of generating analysis code, BioBrain assembles validated analytical methods and can expands its analytical capabilities by integrating existing laboratory scripts into a unified conversational framework. Every selected method and inferred parameter is transparently reported, ensuring traceable and reproducible analyses. On two-channel total internal reflection fluorescence and three-dimensional lattice light-sheet benchmarks, BioBrain exactly reproduces expert-derived results when parameters are specified and degrades predictably and traceably when they are not, while frontier language models generated large, model-dependent quantitative errors despite completing without warning. BioBrain offers a practical path for closing the widening gap between data acquisition and biological discovery, enabling experimental scientists to communicate with computational analysis in the language of biology rather than the language of software.

biophysics↗

bioRxiv2026

Rapid and reliable quantification of cytosolic mRNA escape (RNASCAPE)

Endosomal escape of mRNA remains a critical bottleneck in oligonucleotide therapeutics, with typically less than 5% of delivered mRNA reaching the cytosol. Precise quantification of this escape is hindered by stochastic variability in uptake, release, and expression, while existing methods lack scalability and accuracy. Here we introduce RNASCAPE, a deep learning framework trained on biologically realistic simulations that estimates unlabelled mRNA cytosolic escape efficiency using only three timepoints of EGFP reporter expression and four lipid nanoparticle (LNP) meta-parameters. Benchmarking on synthetic data shows RNASCAPE achieves a mean absolute percentage accuracy of 78%. RNASCAPE accurately predicts escape efficiencies around 5-9% across diverse cell types and revealed that exchanging cholesterol to {beta}-sitosterol drastically reduces mRNA loading and enhances twofold its functional release. By enabling robust, microscopy-agnostic quantification without requiring specialized cell lines or labeled cargo, RNASCAPE provides a scalable framework for benchmarking and rational design of LNP formulations, advancing nucleic acid therapeutic delivery.

biophysics↗

bioRxiv2026

MORPHIS (MORPHological Interpretable Signature) captures heterogeneous treatment- and aging-related responses of single cells

Cell morphology encodes changes in cytoskeletal and organelle organization during disease, treatment, and aging, yet is often assessed qualitatively or through poorly interpretable feature sets extracted from microscopy images. Here we introduce MORPHIS (MORPHological Interpretable Signature), a machine learning framework on explainable, analytically rich features paired with statistical methodologies for robust and interpretable quantification of single-cell morphological signature. MORPHIS extracts compact, interpretable feature signatures that capture both perturbation-specific response magnitude and heterogeneous cellular responses. It accurately distinguishes treatment-specific morphological signatures of eight mechanistically distinct membrane-active and intracellular-targeting compounds in Caco-2 and HeLa cells elucidating conserved and divergent phenotypic responses among compound-classes, as well as ultrastructural nuclear alterations upon aging of C. elegans and quantifies heterogeneous single-cell fractional responses. By remaining cell-type and perturbation agnostic, MORPHIS provides a generalizable framework for quantifying morphological signatures across diverse biological contexts including pharmacological treatment or aging.

biophysics↗

bioRxiv2026

CRISPR-enhanced assessment of variants of unknown significance nominates oncology therapeutic targets and drug repositioning opportunities

Interpreting infrequent somatic variants remains a challenge in cancer genomics. We developed CRISPR-VUS, a framework that uses public Cancer Dependency Map data to identify Dependency-Associated Mutations (DAMs) - variants linked to increased host-gene dependency - with resolution extending to singleton events. Analysis of 977 cell lines across 36 cancer types identified 2,376 DAMs in 1,383 genes, including 1,260 not established as cancer drivers. DAM-bearing genes converge on oncogenic networks, while recurrence in histology-matched tumours, functional-impact predictions, tractability and pharmacological associations enable systematic prioritisation. Prime editing showed that the prioritised NSCLC-specific RTN4IP1-A80T DAM conferred a significant competitive growth advantage in a lung epithelial model, nominating a candidate driver allele. Exploratory pharmacological testing showed a greater maximal response to istaroxime in ATP1B3-I189M-bearing than in ATP1B3-wild-type cells. CRISPR-VUS combines dependency-based rare-variant discovery with evidence-guided prioritisation to nominate candidate drivers, therapeutic targets and drug-repositioning hypotheses. Interactive results are available at https://vus-portal.fht.org/.

bioinformatics↗

bioRxiv2025

Polymer functionalized liposomes as universal nanocarriers for drug delivery: Single particle insights on size-dependent performance and intracellular behavior

Nanomedicine requires smart delivery systems that are precise, robust, and universal. While liposomes are established vehicles in drug delivery, their full potential is challenged by limited stability, leakage, insufficient response and limited insight into particle size dependent performance. Here, we provide polymer-modified liposomes (PMLs), engineered for high structural integrity, broad cargo compatibility, and stimuli-responsive cargo release. We thoroughly characterize PMLs at the single particle level shedding light on key structure-function relationships within polydisperse formulations revealing that small vesicles (<100 nm) displayed significantly higher cargo packing densities, while release was independent of vesicle size. PMLs display high versatility effectively encapsulating cargo types ranging from positively or negatively charged small molecules, to oligonucleotides, and proteins. Studies on PMLs interaction with cell membrane show that PMLs maintain high internalization rate in HeLa and hCMEC/D3 brain cells and achieve [~]50% reduction in cell viability within 24 hours when loaded with the anticancer drug 5-fluorouracil. Finaly, PMLs successfully deliver siRNA targeting eGFP in HEK293-d2eGFP cells, achieving a 10-12% knockdown of eGFP expression, as resolved by machine learning-driven single-cell analysis. This work establishes a framework for PMLs high-resolution functional profiling and opens the way for the next generation rational design of tunable PMLs for drug delivery.

biophysics↗

bioRxiv2024

Direct observation of assembly and function of trigger responsive lipase biohybrids

Protein-polymer biohybrids mark a cutting edge in the creation of advanced materials designed for high performance under diverse conditions by combining the intrinsic stability and adaptability of synthetic polymers with the remarkable functionality and specificity of proteins. Despite the existence of stimuli responsive polymers, their potential for achieving precise, trigger responsive control over both the function and the assembly of protein-polymer biohybrids has yet to be fully attained. Here, we report the synthesis and thorough characterization of pH and temperature responsive lipase-polymer conjugates at both the supramolecular and the single molecule level. In contrast to conventional ensemble measurements performed in solution, we extensively characterized the stimuli triggered reversibility of the self-assembly of these lipase-based biohybrids and recorded the enzymatic activity at the fundamental level of individual nanoparticles. Our findings unexpectedly demonstrated that the stimuli responsive biohybrids exhibited not only a twofold increased enzymatic activity as compared to native lipases in certain cases but also maintained the trigger responsive control over enzymatic activity by temperature. Direct single particle recordings of biohybrid activity showed a correlation of the biohybrid size to catalytic activity, revealing individual enzymes to display higher activity in smaller nanoparticles. The biohybrids exhibit impressive long-term stability, in some cases almost 95% of the enzymatic activity as compared to [~]40-60% for native lipases after 1 year of storage. The improved stability and activity as compared to native enzymes accompanied with their triggered responsiveness highlight their significant potential for tightly controlled biocatalysis and sustainable industrial applications.

biophysics↗

bioRxiv2024

Constitutive Endolysosomal Perforation in Neurons allows Induction of alpha-Synuclein Aggregation by Internalized Pre-Formed Fibrils

The endocytic pathway is both an essential route of molecular uptake in cells and a potential entry point for pathology-inducing cargo. The cell-to-cell spread of cytotoxic aggregates, such as those of -synuclein (-syn) in Parkinsons Disease (PD), exemplifies this duality. Here we used a human iPSC-derived induced neuronal model (iNs) prone to death mediated by aggregation in late endosomes and lysosomes of endogenous -syn, seeded by internalized pre-formed fibrils of -syn (PFFs). This PFF-mediated death was not observed with parental iPSCs or other non-neuronal cells. Using live-cell optical microscopy to visualize the read out of biosensors reporting endo-lysosome wounding, we discovered that up to about 10% of late endosomes and lysosomes in iNs exhibited spontaneous constitutive perforations, regardless of the presence of internalized PFFs. This wounding, absent in parental iPSCs and non-neuronal cells, corresponded to partial damage by nanopores in the limiting membranes of a subset of endolysosomes directly observed by volumetric focused ion beam scanning electron microscopy (FIB-SEM) in iNs and in CA1 pyramidal neurons from mouse brain, and not found in iPSCs or in other non-neuronal cells in culture or in mouse liver and skin. We suggest that the compromised limiting membranes in iNs and neurons in general are the primary conduit for cytosolic -syn to access PFFs entrapped within endo-lysosomal lumens, initiating PFF-mediated -syn aggregation. Significantly, eradicating the intrinsic endolysosomal perforations in iNs by inhibiting the endosomal Phosphatidylinositol-3-Phosphate/Phosphatidylinositol 5-Kinase (PIKfyve kinase) using Apilimod or Vacuolin-1 markedly reduced PFF-induced -syn aggregation, despite PFFs continuing to enter the endolysosomal compartment. Crucially, this intervention also diminished iN death associated with PFF incubation. Our results reveal the surprising presence of intrinsically perforated endo-lysosomes in neurons, underscoring their crucial early involvement in the genesis of toxic -syn aggregates induced by internalized PFFs. This discovery offers a basis for employing PIKfyve kinase inhibition as a potential therapeutic strategy to counteract synucleinopathies.

cell biology↗

bioRxiv2019

Large body size variation is linked to low communication success in tandem running ants

Diversity in animal groups is often assumed to increase group performance. In insect colonies, genetic, behavioral and morphological variation among workers can improve colony functioning and resilience. However, it has been hypothesized that during communication processes, differences between workers, e.g. in body size, could also have negative effects. Tandem running is a common recruitment strategy in ants and allows a leader to guide a nestmate follower to resources. A substantial proportion of tandem runs fail because leader and follower loose contact. Using the ant Temnothorax nylanderi as a model system, we tested the hypothesis that tandem running success is impaired if leader and follower differ in size. Indeed, we found that the success rate of tandem pairs drops considerably as size variation increases: only ~7% of tandem runs were successful when the leader-follower size difference exceeded 10%, whereas 80% of tandem runs were successful when ants differed less than 5% in body length. One possible explanation is that ant size is linked to the preferred walking speed. Ants did not choose partners of similar size, but extranidal workers were larger than intranidal workers, which could reduce recruitment mistakes because it reduced the chance that very large and very small ants perform tandem runs together. Our results suggest that phenotypic differences between interacting workers can have negative effects on the efficiency of communication processes. Whether phenotypic variation has positive or negative effects is likely to depend on the task and the phenotypic trait that shows variation.

animal behavior and cognition↗