Biology subjects

Oskolkov, N.

Publications and source records attributed to Oskolkov, N..

10 recordsLinked to original sources

bioRxiv2026

Sedimentary ancient DNA reveals rhizosphere-like plant-microbe association signals in a 2-million-year-old Arctic ecosystem

Plant-microbe interactions in the rhizosphere are central to nutrient cycling and ecosystem functioning. Sedimentary ancient DNA (sedaDNA) is a promising yet underexplored tool for reconstructing past microbial communities and investigating ecological interactions among plants, animals, and microorganisms. Here, we reanalyse the previously published Kap Kobenhavn Formation (Northern Greenland) sedaDNA dataset to move beyond taxonomic ecosystem reconstruction and test whether ancient sediments preserve structured, rhizosphere-compatible plant-microbe association signals. Our results show that this ancient boreal ecosystem hosted several rhizosphere-associated taxa, comparable to those in modern boreal soils. Several bacterial genera co-occurred repeatedly with specific plant families, forming a rhizosphere-like taxonomic core with predicted plant-growth-promoting traits related to nutrient acquisition, colonisation, and stress tolerance. Although sedaDNA co-occurrence cannot demonstrate direct symbiosis, the consistency of taxonomic, network, and functional signals suggests that ancient sediments preserve interconnected ecological structure. Our findings extend sedaDNA-based ecosystem reconstruction beyond taxonomy and provide a possibility for investigating plant-microbe association signals in deep time.

plant biology↗

bioRxiv2026

Recovery of genomic and transcriptomic profiles from decades-old FFPE brain tissues

Neurological, neurodegenerative, and psychiatric disorders impose substantial morbidity and disability worldwide, yet their molecular basis remains incompletely understood, in part due to limited access to human brain tissue. The Danish Brain Collection, comprising brains from individuals who lived in Danish psychiatric institutions from the 1940s to the 1980s, represents a unique but largely untapped resource for retrospective molecular investigation. Here, we assess the feasibility of extracting and sequencing DNA and RNA from decades-old FFPE brain tissue. We systematically evaluate how extraction and library preparation strategies influence nucleic acid yield and quality, and show that RNA end-repair prior to library preparation substantially enhances transcript diversity, improving data quality from highly degraded samples. Despite extensive fragmentation, we recover biologically informative transcriptomic profiles, including protein-coding and microRNA expression profiles that retain tissue-specific signatures. These results establish the Danish Brain Collection as a viable resource for genomic and transcriptomic analyses and demonstrate the broader potential of archival FFPE tissues for large-scale molecular studies.

molecular biology↗

bioRxiv2026

DNAharvester: A Nextflow Pipeline for Analysing Highly Degraded DNA from Ancient and Historical Specimens

Ancient DNA (aDNA) research has advanced rapidly with the development of high-throughput sequencing, enabling genome-wide analyses of large collections of prehistoric specimens. However, analysing palaeontological and archaeological material with highly degraded DNA constitutes a major bioinformatic challenge. DNA from such samples is characterised by short fragment lengths, low endogenous content, post-mortem damage, and cross-species contamination, which can increase spurious mapping and reference bias, affecting downstream population genetic inferences. We present DNAharvester, a modular and reproducible pipeline designed specifically for processing highly degraded DNA from ancient and historical specimens. DNAharvester integrates metagenomic filtering, competitive mapping, adaptive aligner selection (incorporating BWA-aln, BWA-mem, and Bowtie2), and systematic evaluation of reference bias and spurious mapping. By incorporating flexible mapping and filtering strategies, the pipeline can be adapted to varying sample preservation, focusing on maximising authentic data recovery. DNAharvester features subworkflows for iterative assembly of mitogenomes, identification of genomic repeats and CpG sites, taxonomic classification, microbial/pathogen screening, genetic sex determination, and variant calling. To accommodate varying sequencing depths, the pipeline supports diploid variant calling, genotype likelihood estimation, and pseudo-haploid random allele calling. Implemented in Nextflow, DNAharvester provides a highly scalable, containerised framework that enhances reproducibility, portability, and robustness in aDNA analyses. We validated the pipeline using simulated and empirical datasets, demonstrating its ability to systematically mitigate complex background contamination while preserving authentic genomic signals. By streamlining complex bioinformatic tasks through simple configuration files, DNAharvester establishes a standardised approach for analysing aDNA datasets and makes genomic analyses of ancient remains accessible to the broader research community.

bioinformatics↗

bioRxiv2025

Refining filtering criteria for accurate taxonomic classification of ancient metagenomic data

Taxonomic profiling is a key component of ancient metagenomic analysis, however it is also susceptible to false-positive identifications. In particular, classification tools from the Kraken family, such as Kraken2 and KrakenUniq, are highly sensitive to the choice of filtering options. To address this issue, various filtering approaches have been proposed. In this study, I conduct a comprehensive benchmarking of different filtering strategies using simulated microbial and environmental ancient metagenomic data. I evaluate these approaches based on the balance between sensitivity and specificity of ground truth reconstruction (F1-score), and propose an optimal thresholding strategy tailored to specific sequencing depths in ancient metagenomic datasets.

bioinformatics↗

bioRxiv2025

Disinfecting eukaryotic reference genomes to improve taxonomic inference from ancient environmental metagenomic data

Ancient environmental DNA is increasingly essential for reconstructing past ecosystems, particularly when palaeontological and archaeological tissue remains are absent. Detecting ancient plant and animal DNA in environmental samples often relies on using extensive eukaryotic reference genome databases for profiling shotgun metagenomics data. However, microbial contamination in these references can introduce substantial biases in taxonomic assignments, especially given the typical low abundance of plant and animal DNA in such samples. In this study, we present a method for identifying bacterial and archaeal-like sequences in eukaryotic genomes and apply it to nearly 3,000 reference genomes from NCBI RefSeq and GenBank (vertebrates, invertebrates, plants) as well as the 1,323 PhyloNorway plant genome assemblies from herbarium material from northern high-latitude regions. Our analysis reveals microbial-like sequences in many eukaryotic reference genomes, which are most pronounced in the PhyloNorway dataset. We provide a detailed map of the microbial-like regions, including genomic coordinates and taxonomic annotations. This resource enables the masking of microbial-like regions during profiling analyses, thereby improving the reliability of ancient environmental metagenomic datasets for downstream analyses.

genomics↗

bioRxiv2024

Unravelling the ancient fungal DNA from the Iceman's gut

Here, we explore the possible ancient fungal species in the gut of Otzi, the Iceman, a naturally mummified human found in the Tyrolean Alps (border between Italy and Austria). While ancient DNA (aDNA) has been extensively used to study human, animal, and plant evolution, this research focuses on ancient microbial diversity, specifically fungi. Fungal DNA is often underestimated in metagenomic samples, however here we hypothesise the possibility of retrieving ancient fungal sequences from Otzis gut. A robust bioinformatic pipeline has been developed to detect and authenticate fungal aDNA from stomach, small intestine, and large intestine samples. We revealed the presence of Pseudogymnoascus genus, with P. destructans and P. verrucosus as possible species, that were particularly abundant in the stomach and small intestine. We suggest that Otzi may have consumed these fungi accidentally, likely in association with other elements of his diet, and they thrived in his gut after his death due to their adaptability to harsh and cold environments. This research provides insight into the coexistence of ancient humans with specific fungal species and proposes and validates a conservative bioinformatic approach for detecting fungal aDNA in historical metagenomic samples. Significance statementDespite their essential interactions with all kingdoms of life, limited molecular studies have focused on ancient fungi. Here, we developed a thorough bioinformatic pipeline that allowed us to detect the presence of ancient DNA likely belonging to Pseudogymnoascus destructans and P. verrucosus in the gut of Otzi, a human naturally mummified over 3,000 years ago in the Tyrolean Alps. Both species can survive harsh environmental conditions, and P. destructans is known for its pathogenicity, suggesting that Otzi may have accidentally ingested them and providing valuable insights into how ancient humans coexisted with specific fungal species. We propose a highly reliable methodology for detecting ancient fungal DNA in metagenomic studies of historical samples that can have broader applications to understand ancient ecosystems and their interactions.

microbiology↗

bioRxiv2023

The landscape of ancient human pathogens in Eurasia from the Stone Age to historical times

Infectious diseases have had devastating impacts on human populations throughout history, but important questions about their origins and past dynamics remain1. To create the first archaeogenetic-based spatiotemporal map of human pathogens, we screened shotgun sequencing data from 1,313 ancient humans covering 37,000 years of Eurasian history. We demonstrate the widespread presence of ancient bacterial, viral and parasite DNA, identifying 5,486 individual hits against 492 species from 136 genera. Among those hits, 3,384 involve known human pathogens2, many of which were detected for the first time in ancient human remains. Grouping the ancient microbial species according to their likely reservoir and type of transmission, we find that most groups are identified throughout the entire sampling period. Intriguingly, zoonotic pathogens are only detected [~]6,500 years ago, peaking [~]5,000 years ago, coinciding with the widespread domestication of livestock3. Our findings provide the first direct evidence that this lifestyle change resulted in an increased infectious disease burden. Importantly, they also suggest that the spread of these pathogens increased substantially during subsequent millenia, coinciding with the pastoralist migrations from the Eurasian Steppe4,5.

evolutionary biology↗

bioRxiv2022

aMeta: an accurate and memory-efficient ancient Metagenomic profiling workflow

Analysis of microbial data from archaeological samples is a rapidly growing field with a great potential for understanding ancient environments, lifestyles and disease spread in the past. However, high error rates have been a long-standing challenge in ancient metagenomics analysis. This is also complicated by a limited choice of ancient microbiome specific computational frameworks that meet the growing computational demands of the field. Here, we propose aMeta, an accurate ancient Metagenomic profiling workflow designed primarily to minimize the amount of false discoveries and computer memory requirements. Using simulated ancient metagenomic samples, we benchmark aMeta against a current state-of-the-art workflow, and demonstrate its superior sensitivity and specificity in both microbial detection and authentication, as well as substantially lower usage of computer memory. aMeta is implemented as a Snakemake workflow to facilitate use and reproducibility.

bioinformatics↗

bioRxiv2022

Epigenetic modulators link mitochondrial redox homeostasis to cardiac function

Excessive production of reactive oxygen species (ROS) is characteristic of numerous diseases, but most studies in this area have not considered the impact of endogenous antioxidative defenses. Here, utilizing multi-omics, we demonstrate that in cardiomyocytes mitochondrial isocitrate dehydrogenase (IDH2) constitutes a major antioxidant defense. In both male and female mice and humans the paradoxical reduction in expression of IDH2 associated with heart failure is compensated for by an increase in the enzymes activity. We describe extensive mutual regulation of the antioxidant activities of IDH2 and NRF2 by a network involving 2-oxoglutarate and L2-hydroxyglutarate and mediated in part through unconventional hydroxymethylation of cytosine residues present in introns. Conditional targeting of ROS in a murine model of heart failure improves cardiac function. Together, these insights may explain why previous attempts to treat heart failure with antioxidants have been unsuccessful and open new approaches to personalizing and, thereby, improving such treatment. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/485908v1_ufig1.gif" ALT="Figure 1"> View larger version (66K): org.highwire.dtl.DTLVardef@1032ebeorg.highwire.dtl.DTLVardef@1f1c7bforg.highwire.dtl.DTLVardef@70f6a0org.highwire.dtl.DTLVardef@4fafbc_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIParadoxical downregulation of mitochondrial isocitrate dehydrogenase (IDH2) in response to oxidative stress leads to the discovery of a robust antioxidative defense in the heart. C_LIO_LIAn antioxidative loop involving IDH2 coordinates other antioxidative defenses, such as NRF2. C_LIO_LIThis loop produces epigenetic modifications that link oxidative stress to mitochondrial function. C_LIO_LIThe conclusion that enhancing antioxidative capacity improves cardiac function only when the endogenous capacity is insufficient opens new approaches to individualized treatment of patients with heart failure. C_LI

molecular biology↗

bioRxiv2019

Influence of genetic variants on gene expression in human pancreatic islets - implications for type 2 diabetes

Most signals detected by genome-wide association studies map to non-coding sequence and their tissue-specific effects influence transcriptional regulation. However, many key tissues and cell-types required for appropriate functional inference are absent from large-scale resources such as ENCODE and GTEx. We explored the relationship between genetic variants influencing predisposition to type 2 diabetes (T2D) and related glycemic traits, and human pancreatic islet transcription using RNA-Seq and genotyping data from 420 islet donors. We find: (a) eQTLs have a variable replication rate across the 44 GTEx tissues (<73%), indicating that our study captured islet-specific cis-eQTL signals; (b) islet eQTL signals show marked overlap with islet epigenome annotation, though eQTL effect size is reduced in the stretch enhancers most strongly implicated in GWAS signal location; (c) selective enrichment of islet eQTL overlap with the subset of T2D variants implicated in islet dysfunction; and (d) colocalization between islet eQTLs and variants influencing T2D or related glycemic traits, delivering candidate effector transcripts at 23 loci, including DGKB and TCF7L2. Our findings illustrate the advantages of performing functional and regulatory studies in tissues of greatest disease-relevance while expanding our mechanistic insights into complex traits association loci activity with an expanded list of putative transcripts implicated in T2D development.

genomics↗