Biology subjects

Navolic, J.

Publications and source records attributed to Navolic, J..

4 recordsLinked to original sources

bioRxiv2026

Structural basis of CO2 valence coding in Drosophila

In the olfactory system, glomerular sensory channels of single receptor identity support reliable odor recognition for appropriate approach or avoidance behaviors. For many olfactory stimuli, the assigned sensory value is innate but modulated by the internal state and previous experiences. How context-dependent modulation of innate valence coding supports distinct behavioral responses is poorly understood. Here we show that CO2 sensory information in Drosophila, intrinsically aversive but modified by attractive food signals, diverges from the canonical glomerular channel already in the antennal lobe and is relayed via the polarized local interneuron LN23. LN23 relays sensory input via an extraglomerular CO2 pathway and manipulation of LN23 activity revealed a dominant role in CO2-induced avoidance behavior. The extraglomerular CO2 pathway projects to the posterior lateral protocerebrum (PLP) adjacent to the canonical Lateral Horn (LH) olfactory processing center and segregates into anatomically distinct valence channels. Connectome data together with functional characterization showed the convergence of parallel CO2 channels onto two interconnected third-order neurons. These neurons integrate additional sensory modalities via distinct mechanisms: while the glomerular CO2 pathway converges with food relay neurons onto separated dendritic domains of the PD5 interneuron in the LH, the extraglomerular pathways integrating CO2 information with antennal humidity and temperature modalities establish antagonistic inputs onto the PLP interneuron PV9. This early anatomical divergence of a defined olfactory channel followed by separated multi-modal integration provides a structural basis for context-dependent valence coding and appropriate behavioral responses.

neuroscience↗

bioRxiv2025

Expression of LTR and LINE1 transposable elements defines atypical teratoid/rhabdoid tumor subtypes

Atypical teratoid rhabdoid tumors (ATRTs) are aggressive central nervous system tumors mainly affecting young children. Extensive molecular characterization based on gene expression and DNA methylation patterns has solidly established three major ATRT subtypes (MYC, SHH and TYR), which show distinct clinical features, setting the basis for more effective, targeted treatment regimens. Transcriptional activity of transposable elements (TEs), like LINE1s and LTRs, is tightly linked with human cancers as a direct consequence of lifting epigenetic repression over TEs. The sole recurrent biallelic loss-of-function mutation in SMARCB1 in ATRTs, a core component of the SWI/SNF chromatin remodeling complex, raises the question of how TE transcription contributes to ATRT development. Here, we comprehensively investigate the transcriptional profiles of 1.9M LINE1 and LTR elements across ATRT subtypes in primary human samples. We find TE transcription profiles are unique, allowing sample stratification into ATRT subtypes. The TE activity signature in ATRT-MYC subtype is unique, setting these tumors apart from SHH and TYR ATRTs. More specifically, ATRT-MYC shows broadly reduced transcript levels of LINE1 and ERVL-MaLR subfamilies. ATRT-MYC is also unique in having significantly less LTR and LINE1 loci with bidirectional promoter activity. Furthermore, we identify 849 differentially transcribed TEs in primary samples, which are predictive towards established ATRT-SHH and-MYC cell line models. In summary, including TE transcription profiles into the molecular characterization of ATRTs might reveal new tumor vulnerabilities leading to novel therapeutic interventions, such as immunotherapy.

cancer biology↗

bioRxiv2025

OmixLitMiner 2: Guided Literature Mining Tools for Automated Categorization of Marker Candidates in Omics Studies

Omics analyses are crucial for understanding molecular mechanisms in biological research. The vast quantity of detected biomolecules presents a significant challenge in identifying potential biomarkers. Traditional methods rely heavily on labor-intensive literature mining to extract meaningful insights from long lists of regulated candidates. To address this, we developed OmixLitMiner 2 to improve the efficiency of omics data interpretation, increase the speed for the validation of results and accelerate further evaluation based on the selection of marker candidates for subsequent experiments. The updated tool utilizes UniProt for synonym and protein name retrieval and employs the PubMed database as well as PubTator 3.0 for mining abstracts and full texts of available biomedical literature. It allows for advanced keyword-based searches and provides classification of proteins or genes with respect to their awareness level in relationship to scientific questions. OmixLitMiner 2 offers improved functionality over the previous version and comes with a user-friendly Google Colab interface. In comparison to the previous version OmixLitMiner 2 improves the retrieval and classification of relevant publications. The tool significantly reduces the time required for manual searches, as demonstrated in a case study involving proteomic data from spatially resolved mouse brain cortex layers. Statement of SignificanceWe developed OmixLitMiner 2 to determine, for a given set of marker candidates, the extent to which they have been described in the literature. The tool is easy-to-use and can quickly generate a categorized list of references obtained by automated literature searches for protein and gene names and involving keywords related to a specific scientific question. The categorization provides a ranking of how well-studied the genes or proteins: Candidates of category 1 are well-known regarding the scientific question; Candidates of category 2 have been mentioned in a publication associated with the specific scientific question; Candidates of category 3 have never been described to be associated with the specific scientific question; Candidates of category 4 are not yet known proteins and are not associated with a gene name. This classification can aid in the decision, which protein or gene candidates to choose for follow-up experiments.

bioinformatics↗

bioRxiv2024

Co-activation of LIN28A and CTNNB1 disturbs cortical neuronal migration and pia mater integrity

Developmental signalling pathways act in stage and tissue dependent relation and mis-activation can drive tumour formation. The RNA-binding protein LIN28A maintains stemness and is overexpressed in embryonal brain tumours. Activating mutations of CTNNB1 - the WNT pathway effector - have been reported in respective brain tumours. The aim of this study was to investigate the interplay of these oncogenic proteins during embryonal brain development. The combination of both oncogenic factors did not lead to brain tumour formation but resulted in disturbed lamination and impaired cell migration in the cerebral cortex. Spatially resolved proteome analysis revealed imbalances of the extracellular matrix protein LAMB1 and its receptors RPSA and ITGB1 accompanied by a porous pial border and overmigration of neural cells. Cajal-Retzius cells were misplaced in deeper cortex regions without affecting general REELIN levels and additional reduced levels of -DYSTROGLYCAN. Taken together, the interplay of LIN28A and CTNNB1 resulted in a cortical migration disorder showing histomorphological and molecular similarities to human Cobblestone lissencephaly (type 2), highlighting novel implications of the oncogene LIN28A in extracellular matrix integrity.

neuroscience↗