Biology subjects

Wilczynski, B.

Publications and source records attributed to Wilczynski, B..

13 recordsLinked to original sources

bioRxiv2026

Systematic review and transcriptomic meta-analysis of environmental enrichment reveal core molecular programs of brain plasticity

RATIONALEEnvironmental enrichment (EE) paradigms in rodents have long demonstrated that enhanced sensory, cognitive, social, and motor stimulation positively impacts brain function, improving learning, memory, and neuroplasticity. These effects have significant implications for understanding cognitive development and mitigating cognitive decline and brain aging. While numerous transcriptomic studies have explored EE-induced molecular changes, a unified view of the genes and pathways consistently modulated remains lacking. METHODSTo address this gap, we performed a systematic review and meta-analysis. We conducted a comprehensive PubMed search for all studies published up to February 2025 that matched all the following inclusion criteria: (1) employed EE paradigms; (2) were conducted on rodents; (3) utilized genome-wide transcriptomic methods; (4) examined brain regions or neuronal populations. The 323 retrieved articles were manually screened for relevance to the study aims and data availability. Datasets from 20 eligible RNA-seq reports were reprocessed using a unified analysis pipeline and subjected to a meta-analysis with three complementary statistical methods. RESULTSDespite considerable heterogeneity across studies, our integrative analysis identified consistent gene expression signatures linked to synaptic function, plasticity and their transcriptional regulation. These molecular insights advance our understanding of how EE impacts on neuronal and behavioural outcomes, and may inform therapeutic strategies aimed at replicating or enhancing EE benefits. To promote open science and foster further research, we developed an accessible web application, mEEtaBrain, that enables the neuroscience community to navigate and interrogate our meta-analysis results.

neuroscience↗

bioRxiv2025

Rearing conditions bidirectionally modulate cognitive abilities and AP-1 signaling in hippocampal neurons in a cell type-specific manner.

Environmental conditions profoundly influence cognitive development, particularly during early life. Transcriptional and epigenetic mechanisms may serve as molecular substrates for the lasting effects of environmental enrichment (EE) and impoverishment (IE) on cognitive abilities and hippocampal function. However, the specific gene programs driving these changes remain largely unknown. In this study, EE and IE modulated the cognitive abilities of mice in opposing directions. By combining hippocampal microdissection and genetic tagging of neuronal nuclei with genome-wide analyses of gene expression, chromatin accessibility, histone acetylation, and DNA methylation, we uncovered profound differences in the transcriptional and epigenetic profiles of CA1 pyramidal neurons and dentate gyrus (DG) granule neurons. These analyses revealed cell type-specific genomic changes induced by EE and IE, highlighting distinct patterns of neuroadaptation within each population. This multiomic screen pinpointed the activity-regulated transcription factor AP-1 as a crucial mediator of neuroadaptation to conditions during early life in both cell types, albeit through distinct downstream mechanisms. Conditional deletion of Fos, a core AP-1 subunit, in excitatory neurons hampered EE-induced cognitive enhancement, further underscoring the pivotal role of this transcription factor in neuroadaptation.

neuroscience↗

bioRxiv2024

Chitinase-1 inhibition reverses metabolic dysregulation and restores homeostasis in MASH animal models

OATD-01 is a chitinase-1 (CHIT1) inhibitor, reducing inflammation and fibrosis in animal models where chronic inflammation leads to tissue remodeling. CHIT1, predominantly secreted by macrophages, is overexpressed in metabolic-dysfunction-associated steatohepatitis (MASH). In this study, we demonstrated the efficacy of OATD-01 in two murine and a rat model of MASH. RNA-Seq analysis revealed that OATD-01 reversed MASH-dysregulated genes. Apart from the attenuation of inflammation and fibrosis, OATD-01 regulated metabolic processes such as lipid metabolism and glycolysis. We demonstrated that both genetic and pharmacological inactivation of CHIT1 resulted in inhibition of glycolysis and glucose uptake in primary macrophages. As a consequence, we observed increased ATP, lower citrate and increased acetate levels, resulting in a reduced IL-1{beta} secretion. These results revealed the key role for CHIT1 in regulating metabolism. OATD-01 is a macrophage modulator that can directly restore metabolic balance and consequently inhibit inflammation and fibrosis, supporting its use for MASH treatment.

pharmacology and toxicology↗

bioRxiv2023

Molecular signature of primate astrocytes reveals pathways and regulatory changes contributing to the human brain evolution

Astrocytes contribute to the development and regulation of the higher-level functions of the brain, the critical targets of evolution. However, the molecular signature of foetal astrocyte evolution in primates is unknown. Here, to address this question, we use human, chimpanzee, and macaque induced pluripotent stem cell-derived foetal astrocytes (iAstrocytes). Human iAstrocytes are bigger and more complex than the non-human primate iAstrocytes. We find loci related to the regulation of cell size with increased expression in the human lineage. Likewise, we uncover that genes and mechanisms implicated in long-range intercellular signalling are activated in the human iAstrocytes. Strikingly, loci downregulated in the human lineage frequently relate to intellectual disability raising new questions on the trade-offs associated with the evolution of the human mind. Using our system, through a multilevel regulome analysis and machine learning, we uncover that functional activation of enhancers coincides with a previously unappreciated, pervasive gain of binding sites of stripe transcription factors. In summary, we shed new light on a mechanism driving the acquisition of the regulatory potential of enhancers.

neuroscience↗

bioRxiv2021

A new analytical pipeline reveals metatranscriptomic changes upon high-fat diet in a Down syndrome mouse model.

The existing methods designated for metatranscriptomic studies are still rare and being developed. In this paper we present a new analytical pipeline combining contig assembly, gene selection and functional annotation. This pipeline allowed us to reconstruct contigs with very high unique mappability (83%) and select sequences encoding putative bacterial genes reaching also a very high (66%), unique mappability of the NGS sequencing reads. Then, we have applied our pipeline to study faecal metatranscriptome of a Down syndrome (DS) mouse model, the Ts65Dn mice, in order to identify the differentially expressed transcripts. Recent studies have implicated dysbiosis of gut microbiota in several central nervous system (CNS) disorders, including DS. Given that DS individuals have an increased prevalence of obesity, we also studied the effects of a high-fat diet (HFD) on the transcriptomic changes of mice gut microbiomes, as the complex symbiotic relationship between the gut microbiome and its host is strongly influenced by diet and nutrition. Using our new pipeline we found that compared to wild type (WT), Ts65Dn mice showed an elevated expression levels of genes involved in hypoxanthine metabolism, which contributes to oxidative stress, and a down-regulated expression of genes involved in interactions with host epithelial cells and virulence. Microbiomes of mice fed HFD showed significantly higher expression levels of genes involved in membrane lipopolysaccharides / lipids biosynthesis, and decreased expression of osmoprotection and lysine fermentation genes, among others. We also found evidence that mice microbiota is capable of expressing genes encoding for neuromodulators, which may play a role in development of compulsive overeating and obesity. Our results show a DS-specific metatranscriptome profile and show that a high-fat diet affects the metabolism of mice gut microbiome by changing activity of genes involved in lipids, sugars, proteins and amino acids metabolism and cell membranes turnover. Our new analytical pipeline combining contig assembly, gene selection and functional annotation provides new insights into the metatranscriptomic studies.

bioinformatics↗

bioRxiv2021

Black chromatin is indispensable for accurate simulations of Drosophila melanogaster chromatin structure.

The interphase chromatin structure is extremely complex, precise and dynamic. Experimental methods can only show the frequency of interaction of the various parts of the chromatin. Therefore, it is extremely important to develop theoretical methods to predict the chromatin structure. In this publication, we describe the necessary factors for the effective modeling of the chromatin structure in Drosophila melanogaster. We also compared Monte Carlo with Molecular Dynamic methods. We showed that incorporating black, non-reactive chromatin is necessary for successfully prediction of chromatin structure, while the loop extrusion model or using Hi-C data as input are not essential for the basic structure reconstruction. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=68 SRC="FIGDIR/small/472204v1_ufig1.gif" ALT="Figure 1"> View larger version (10K): org.highwire.dtl.DTLVardef@65d59aorg.highwire.dtl.DTLVardef@1aa9cbforg.highwire.dtl.DTLVardef@18f5cborg.highwire.dtl.DTLVardef@b1034d_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2020

Characterization of the microbiome of Down syndrome mouse model (Ts65Dn) in standard and high-fat diet.

The intestinal microbiota is known to affect its host in numerous ways and can be altered by many factors including the host genotype and high-calorie diets. Down syndrome (DS) is a genetic neurodevelopmental disorder caused by the total or partial triplication of chromosome 21. Recently, a human study reported microbiota differences between DS and euploid humans. To further explore the differences due to the genotype, we here investigated the microbiome of trisomic mice (Ts65Dn). In trisomic mice we found a significant enrichment in abundances of bacteria: Bacteroides ovatus, B. thetaiotaomicron, and Akkermansia muciniphila - the mucus-degrading and gut-health promoting species. Since diet composition has an effect on microbiota species, we studied the effect of a high-fat diet on the observed genotypic differences. Our study provides evidence that microbiomes of trisomic mice on the control diet present more inter-individual differences than WT mice. Moreover, we observed that the high-fat diet led to increased differences between individuals and this effect was even more pronounced in the trisomic than in WT mice. We validated the results obtained with widely used 16rRNA gene sequencing with the sequencing of the total RNA. HighlightsO_LIDown syndrome (DS) model mice faecal microbiomes are characterized by an overrepresentation of Bacteroides ovatus, Bacteroides thetaiotaomicron, and Akkermansia muciniphila species. C_LIO_LIDS mice are characterized by higher heterogeneity of their microbiome communities than WT mice. C_LIO_LIHigh-fat diet leads to more diverse microbiome communities between mice, especially in trisomic genotype. C_LI

genomics↗

bioRxiv2020

Epigenetic regulation of differentially expressed genes between various glioma types

Gliomas are the most frequent primary tumors of the central nervous system (CNS) and encompass two major subgroups: diffuse, malignant gliomas and benign, well differentiated gliomas showing a more circumscribed growth. Genome-wide next generation sequencing studies have uncovered specific genetic alterations, transcriptomic patterns and epigenetic profiles associated with different types of gliomas improving tumor diagnosis and having important implications for future clinical trials and patient management. We have recently created a unique resource encompassing genome-wide profiles of open chromatin, histone H3K27ac and H3Kme3 modifications, DNA methylation and transcriptomes of 33 glioma samples of different grades. Here, we took advantage of a wealth of data from those high-throughput experiments, intersected those data with topologically associating domains (TADs) and demonstrated that the chromatin organization and epigenetic landscape of enhancers have a strong impact on genes differentially expressed in low grade versus high grade gliomas. We identified TADs enriched in glioma grade-specific genes and/or epigenetic marks. We found a set of transcription factors, including REST, E2F1 and NFKB1, that are most likely to regulate gene expression in multiple TADs, containing glioma-related genes. Moreover, many genes associated with the cell-matrix adhesion Gene Ontology group, in particular 14 PROTOCADHERINs, were found to be regulated by the long range contacts with enhancers. Overall, the results presented here demonstrate the existence of epigenetic differences associated with chromatin organization driving differential gene expression in gliomas of different malignancy. We demonstrated that integration of whole genome epigenetic data with Hi-C data and transcriptomic profiles described in this work, can segregate low and high grade gliomas and reveal new regulatory networks that could explain some of the functional differences between gliomas of different malignancies. HighlightsO_LIIntegration of ATAC-seq, ChIP-seq and RNA-seq reveals glioma malignancy-related gene regulatory networks. C_LIO_LITADs segmentation contributes to gene-epigenetically modified enhancer relationships. C_LIO_LIContacts of active enhancers in gliomas of different malignancies might affect expression of genes involved in cancerogenesis, such as PROTOCADHERINs or EGFR. C_LI

cancer biology↗

bioRxiv2019

Mapping chromatin accessibility and active regulatory elements reveals new pathological mechanisms in human gliomas

Chromatin structure and accessibility, and combinatorial binding of transcription factors to regulatory elements in genomic DNA control transcription. Genetic variations in genes encoding histones, epigenetics-related enzymes or modifiers affect chromatin structure/dynamics and result in alterations in gene expression contributing to cancer development or progression. Gliomas are brain tumors frequently associated with epigenetics-related gene deregulation. We performed whole-genome mapping of chromatin accessibility, histone modifications, DNA methylation patterns and transcriptome analysis simultaneously in multiple tumor samples to unravel novel epigenetic dysfunctions driving gliomagenesis. Based on the results of the integrative analysis of the acquired profiles, we created an atlas of active enhancers and promoters in benign and malignant gliomas. We explored these elements and intersected with Hi-C data to uncover molecular mechanisms instructing gene expression in gliomas. SignificanceEpigenetics-driven deregulation of gene expression accompanies cancer development, but its comprehensive characterization in cancer patients is fragmentary. We performed whole-genome profiling of gene expression, open chromatin, histone modifications and DNA-methylation profiles in the same samples from benign and malignant gliomas. Our study provides a first comprehensive atlas of active regulatory elements in gliomas, which allowed identification of the functional enhancers and promoters in patient samples. This comprehensive approach revealed epigenetic patterns influencing gene expression in benign gliomas and a new pathogenic mechanism involving FOXM1-driven network in glioblastomas. This atlas provides a common set of elements for cross-comparisons of existing and new datasets, prompting novel discoveries and better understanding of gliomagenesis. HighlightsO_LIWe provide an atlas of cis-regulatory elements active in human gliomas C_LIO_LIEnhancer-promoter contacts operating in gliomas are revealed C_LIO_LIDiverse enhancer activation is pronounced in malignant gliomas C_LIO_LIChromatin loop activates FOXM1-ANXA2R pathological network in glioblastomas. C_LI

cancer biology↗

bioRxiv2019

DiADeM: differential analysis via dependency modelling of chromatin interactions with generalized linear models

High throughput Chromosome Conformation Capture experiments have become the standard technique to assess the structure and dynamics of chromosomes in living cells. As any other sufficiently advanced biochemical technique, Hi-C datasets are complex and contain multiple documented biases, with the main ones being the non-uniform read coverage and the decay of contact coverage with genomic distance. Both of these effects have been studied and there are published methods that are able to normalize different Hi-C data to mitigate these biases to some extent. It is crucial that this is done properly, or otherwise the results of any comparative analysis of two or more Hi-C experiments are bound to be biased. In this paper we study both mentioned biases present in the Hi-C data and show that normalization techniques aimed at alleviating the coverage bias are at the same time exacerbating the problems with contact decay bias. We also postulate that it is possible to use generalized linear models to directly compare non-normalized data an that it is giving better results in identification of differential contacts between Hi-C matrices than using the normalized data.

bioinformatics↗

bioRxiv2018

BPscore: an effective metric for meaningful comparisons of structural chromosome segmentations

Studying the 3D structure of chromosomes is an emerging field flourishing in recent years because of rapid development of experimental approaches for studying chromosomal contacts. This has led to numerous studies providing results of segmentation of chromosome sequences of different species into so called Topologically Associating Domains (TADs). As the number of such studies grows steadily and many of them make claims about the perceived differences between TAD structures observed in different conditions, there is a growing need for good measures of similarity (or dissimilarity) between such segmentations. We provide here a BP score, which is a relatively simple distance metric based on the bipartite matching between two segmentations. In this paper, we provide the rationale behind choosing specifically this function and show its results on several different datasets, both simulated and experimental. We show that not only the BP score is a proper metric satisfying the triangle inequality, but that it is providing good granularity of scores for typical situations occuring between different TAD segmentations. We also introduce local variant of the BP metric and show that in actual comparisons between experimental datasets, the local BP score is correlating with the observed changes in gene expression and genome methylation. In summary, we consider the BP score a good foundation for analysing the dynamics of chromosome structures. The methodology we present in this work could be used by many researchers in their ongoing analyses making it a popular and useful tool.\n\nAuthor summaryMany researchers are interested in the chromosomal structure, its function and dynamics. Over the recent years, chromosome conformation capture (3C) methods have become the main source of experimental data on the subject and the Topologically Associating Domains (TADs) have become the de-facto standard unit of chromosomal structure. Many methods have been developed for TAD calling and the 3C experiments have been done in multiple conditions giving us a multitude of chromosomal segmentations describing the most atomic differences in chromosomal structure between conditions. Until now, such segmentations were compared mostly by very rough measures, such as the Jaccard coefficient or TAD overlaps or very general metrics like the variation of information coefficient. This has limited the researchers in the analysis of differential TAD segmentations, and practically prevented any proper analysis of TAD dynamics between conditions. Our approach has the potential to facilitate such analyses by providing researchers with mathematically sound metric that is designed specifically for the purpose and tested on both simulated and experimental data. Additionally, we provide a local variant of our measure that is a natural derivative of the BP score that can indicate which parts of the chromosomes are undergoing the most significant structural reorganizations.

bioinformatics↗

bioRxiv2016

Bio.Ontology - Python tools for enrichment analysis and visualization of ontologies

MotivationFunctional annotation and enrichment analysis based on ontologies has become one of the standard methods of analysis of experimental results. Over the past decade, many methods have been proposed for statistical quantification of enrichment of different functional terms and many implementations of these methods are available. As the popularity of these methods grows, the need for tools facilitating their automation increases.\n\nResultsWe present a complete Python library for statistical enrichment analysis of gene sets and gene rankings compatible with most available biological ontologies. It allows the user to perform all necessary steps: reading the ontologies and gene annotations in multiple formats; performing enrichment analysis using various methods and visualizing the results as readable reports. Importantly, our library includes methods for correcting for multiple hypotheses testing including computation of False Discovery Rates.\n\nAvailabilityThe library is compatible with recent versions of python interpreter ([≥] 2.6 or [≥] 3.3) and is available on github at: https://github.com/regulomics/biopython together with an API documentation and a tutorial. The sample galaxy installation can be found at http://regulomics.mimuw.edu.pl/wp/GO/.\n\nContactbartek@mimuw.edu.pl

bioinformatics↗

bioRxiv2016

DiffTAD: Detecting Differential contact frequency in Topologically Associating Domains Hi-C experiments between conditions

MotivationIn recent years, the interest in analyzing chromosome conformation by Hi-C and related techniques has grown. It has been shown that contact frequency matrices obtained by these methods correlate with other methods of measurement of activity such as transcriptomics and histone modification assays. This brings a question of testing for differential contact frequency between experiments to the field.\n\nResultsIn this work, we provide a freely available software that implements two statistical methods for testing the significance of differential contact frequency in topological domains between two experiments. One method follows an empirical, permutation based approach to computing p-values, while the other is a parametric test based on the Poisson-Binomial distribution.\n\nAvailabilityThe software is freely available on the GNU General Public License at https://bitbucket.org/rzaborowski/differential-analysis\n\nContact[r.zaborowski|bartek]@mimuw.edu.pl\n\nSupplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗