Biology subjects

Hajduch, M.

Publications and source records attributed to Hajduch, M..

4 recordsLinked to original sources

bioRxiv2024

Comprehensive multi-omics profiling of a healthy human cohort

Multi-omics approaches can offer powerful insights into personalized biomarker profiles relevant for disease diagnosis, prognosis, and therapeutics. However, separating meaningful biological variability from technical noise remains a major challenge. The EATRIS-Plus consortium analyzed blood samples from 127 healthy adults across six omics layers using twelve platforms, resulting in one of the most comprehensive multi-omics profiling datasets of healthy individuals available to date. We applied reproducible workflows to analyze and integrate these data, revealing several key findings. Sex significantly influenced all omics layers, emphasizing the importance of sex-balanced study designs. Age could be accurately predicted using epigenetic clocks, achieving high performance with our high-resolution enzymatic methylation sequencing data (R2 = 0.90), whereas candidate aging biomarkers were identified across all omics layers. The resulting dataset provides reference ranges in healthy individuals for abundance and variability of omics features, enabling robust power analyses, sample size estimations, and benchmarking of multi-omics integration methods. This resource can guide future biomarker discovery and personalized health research and was made FAIR-compliant and publicly available via the ClinData Portal (https://clindata.imtm.cz) and a Zenodo repository (https://doi.org/10.5281/zenodo.17514796).

bioinformatics↗

bioRxiv2024

Morphological Profiling Dataset of EU-OPENSCREEN Bioactive Compounds Over Multiple Imaging Sites and Cell Lines

Morphological profiling with the Cell Painting assay has emerged as a promising method in drug discovery research. The assay captures morphological changes across various cellular compartments enabling the rapid identification of the effect of compounds. We present a comprehensive morphological profiling dataset using the carefully curated and well-annotated EU-OPENSCREEN Bioactive Compound Set. Our profiling dataset was generated across multiple imaging sites with high-throughput confocal microscopes using the Hep G2 as well as the U2 OS cell line. We employed an extensive assay optimization process to achieve high data quality across the different imaging sites. An analysis of the four replicates validates the robustness of the generated data. We compare morphological features of the different cell lines and map the profiles to activity, toxicity, and basic compound targets to further describe the dataset as well as to demonstrate the potential of this dataset to be used for mechanism of action exploration.

cell biology↗

bioRxiv2023

Differential seeding by exogenous R2 and R3 fibrils influences autophagic degradation of intracellular tau aggregates in Tau K18 P301S cells

Aggregation of misfolded tau protein is a common feature of tauopathies. Cells employ diverse mechanisms to eliminate misfolded tau with different conformations, contributing to the varied clinical and pathological manifestations of tauopathies. This study focuses on the clearance of seeded tau aggregates following the induction of biosensor cells with R2 and R3 fibrils that exhibit distinct aggregation kinetics and seeding potencies. Our hypothesis is that the dissimilarity in time-dependent intracellular seeding induced by R2 and R3 fibrils underlies the variation in autophagy failure. These discrepancies may account for the heterogeneity of pathology and disease progression between 3R and 4R tauopathies, given the absence of R2 in 3R tau isoforms. In R2-induced cells, alterations in p62 and LC3II/I levels, indicative of proteotoxic stress and autophagy failure, occur sooner than in R3-induced cells. Conversely, LAMP1 levels remained unaffected, suggesting a failure in the fusion of aggregate-containing autophagosomes with lysosomes. This autophagic failure may increase seed-dependent intracellular aggregation in induced cells. Consequently, we assessed the impact of autophagy inducers on the clearance of intracellular tau aggregates in induced cells. Epigallocatechin gallate (EGCG) demonstrated the highest efficacy in inducing autophagy and reducing p62 levels, decreasing seeding and clearing aggregates. Overall, this study elucidates the differential effects of prion-like R2 and R3 strains on autophagy and highlights how compounds like EGCG can selectively reduce tau aggregation to treat specific tauopathies. We provide insights into the distinct mechanisms of autophagy failure and autophagy clearance of intracellular aggregates in cells induced with R2 and R3 fibrils.

neuroscience↗

bioRxiv2020

Minimal information for Chemosensitivity assays (MICHA): A next-generation pipeline to enable the FAIRification of drug screening experiments

Chemosensitivity assays are commonly used for preclinical drug discovery and clinical trial optimization. However, data from independent assays are often discordant, largely attributed to uncharacterized variation in the experimental materials and protocols. We report here the launching of MICHA (Minimal Information for Chemosensitivity Assays), accessed via https://micha-protocol.org. Distinguished from existing efforts that are often lacking support from data integration tools, MICHA can automatically extract publicly available information to facilitate the assay annotation including: 1) compounds, 2) samples, 3) reagents, and 4) data processing methods. For example, MICHA provides an integrative web server and database to obtain compound annotation including chemical structures, targets, and disease indications. In addition, the annotation of cell line samples, assay protocols and literature references can be greatly eased by retrieving manually curated catalogues. Once the annotation is complete, MICHA can export a report that conforms to the FAIR principle (Findable, Accessible, Interoperable and Reusable) of drug screening studies. To consolidate the utility of MICHA, we provide FAIRified protocols from five major cancer drug screening studies, as well as six recently conducted COVID-19 studies. With the MICHA webserver and database, we envisage a wider adoption of a community-driven effort to improve the open access of drug sensitivity assays.

bioinformatics↗