Biology subjects

Ivanov, I.

Publications and source records attributed to Ivanov, I..

11 recordsLinked to original sources

bioRxiv2026

Systematic comparison of pathogenic variants of the RNA exosome gene EXOSC3/RRP40 in Saccharomyces cerevisiae reveals variant-specific functional consequences

The RNA exosome is an essential, evolutionarily conserved ribonuclease complex that processes and degrades many classes of RNA. The complex is composed of three structural cap subunits (EXOSC1-3/Csl4, Rrp4, Rrp40; H. sapiens/S. cerevisiae), six structural core subunits (EXOSC4-9/Rrp41,Rrp46,Mtr3,Rrp42,Rrp43,Rrp45), and a catalytic ribonuclease (DIS3 or DIS3L/Dis3). Cofactors that associate with the RNA exosome confer specificity to target specific RNAs for processing and/or decay. Missense mutations in genes encoding structural subunits of the RNA exosome have been linked to neurological diseases. Notably, several pathogenic mutations have been identified in EXOSC3 that are associated with pontocerebellar hypoplasia type 1b (PCH1b). These pathogenic alleles cause a broad spectrum of clinical severity, suggesting variant-specific functional consequences. Given the high degree of conservation between the human and budding yeast RNA exosome complexes, we performed a systematic analysis of eight pathogenic EXOSC3 variants modeled in budding yeast Rrp40. We find that two Rrp40 variants cause growth defects, show distinct negative genetic interactions with RNA exosome cofactor mutants, and impair RNA processing in budding yeast. One of these variants, EXOSC3-Y109N/Rrp40-Y64N, had not been previously characterized in any mechanistic studies. Computational stability predictions and immunoblot analyses indicate that most EXOSC3/Rrp40 variants display reduced steady-state protein levels, but decreased protein levels do not strictly correlate with phenotype or disease severity, suggesting that individual variants disrupt RNA exosome function through distinct mechanisms. Collectively, our studies suggest that pathogenic EXOSC3 variants alter RNA exosome function through distinct mechanisms and provide insight into the specific molecular defects that could underlie pathology.

genetics↗

bioRxiv2026

Orchestrated metal ion repositioning defines the dynamic catalytic strategy of the essential DNA repair nuclease APE1

Human AP-endonuclease 1 (APE1) is a vital enzyme in the base excision repair pathway that protects genome stability by eliminating ubiquitous abasic DNA lesions. Despite its importance and therapeutic potential, how APE1 achieves high specificity and single-metalion catalytic efficiency remains unclear. Here, we present a high-resolution structure of the APE1-DNA Michaelis complex coordinated with physiological cofactor Mg2+. Integrating this snapshot with ab initio molecular dynamics and metadynamics simulations reveals a novel "moving metal ion" mechanism in which Mg2+ undergoes orchestrated repositioning to trigger a concerted catalytic reaction, bypassing the formation of an associative pentavalent intermediate. This distinct catalytic strategy, driven by concerted active-site reorganization, enables APE1 to efficiently process damaged DNA using only one metal ion cofactor. A previously unrecognized hydrogen-bonding network couples catalytic water activation to the metal ion movement - two events that strikingly occur on opposite sides of the active site. These findings provide a blueprint for how enzymes synchronize distal active site rearrangements with transition state formation. Our results further suggest that effective AI-targeted inhibitor design should develop capacities to predict mechanistically critical non-canonical rotamers and transient hydrogen-bonding networks. Our combined findings offer a foundation for the design of inhibitors targeting APE1 overexpression in cancer.

biochemistry↗

bioRxiv2025

Inhibitory control and error processing in Obsessive-Compulsive Disorder: A mega-analysis of task-based fMRI data by the ENIGMA-OCD consortium

ObjectiveObsessive-compulsive disorder (OCD) is a chronic condition in which impaired inhibitory control and excessive error monitoring may contribute to the maintenance of obsessions and compulsions. This mega-analysis investigates neural activation during response inhibition and error processing using adult and pediatric data from the ENIGMA-OCD consortium and the ABCD study. MethodsIndividual participant data was uniformly processed using HALFpipe to extract statistical maps for response inhibition and error processing contrasts. Bayesian multilevel models were used to assess regional and whole-brain effects of OCD, with additional analyses examining the association between the OCD clinical profile and task-related activation. ResultsAcross inhibitory control tasks, both individuals with OCD and control participants showed robust activation in regions implicated in response inhibition and error processing. During response inhibition, compared to controls, adults with OCD showed stronger somatomotor cortex activation, while children with OCD showed stronger occipital cortex activation. Children with likely OCD from the ABCD cohort showed reduced activity in the frontoparietal network in the anterior insula/frontal operculum region. During error processing, relative to controls, adults with OCD showed weaker activation in fronto-striatal regions, while children with OCD showed stronger activation in frontoparietal and attention networks. Greater OCD symptom severity was associated with weaker task-related activation in adults and stronger activation in children during response inhibition. ConclusionCase-control differences in brain activation during inhibitory control varied by age group and task contrast. Symptom severity emerged as the main clinical correlate of activation during inhibition, suggesting that inhibitory control deficits in OCD may be both state-dependent and developmentally specific.

neuroscience↗

bioRxiv2025

Executive control in Obsessive-Compulsive Disorder: A worldwide mega-analysis of task-based functional neuroimaging data of the ENIGMA-OCD consortium

ObjectiveObsessive-compulsive disorder (OCD) is associated with impaired executive function and altered activity in associated neural circuits, contributing to reduced goal-directed behavior. To investigate neural activation during executive control, we conducted a mega-analysis in the ENIGMA-OCD consortium pooling individual participant data from 475 individuals with OCD and 345 healthy controls across 15 fMRI tasks collected worldwide. MethodsIndividual participant data was uniformly processed using HALFpipe to construct voxelwise statistical images of executive control and task load contrasts. Parameter estimates extracted from regions of interest were entered into multilevel Bayesian models to examine regional and whole-brain effects of diagnosis, and, within OCD, the influence of medication status, symptom severity, and age of onset on task activation. ResultsWe observed a robust task activation pattern across individuals with OCD and control participants in executive control regions across tasks. Relative to controls, individuals with OCD showed moderate to very strong evidence of weaker activation of the dorsolateral prefrontal cortex, precuneus, frontal eye fields, and inferior parietal lobule during executive control (all positive posterior probabilities [P+]<0.1). Individuals with OCD also showed stronger activation in regions of the default mode network during executive function relative to controls. We found little evidence for differential activation during executive control in task- positive regions related to disease onset, severity and medication status. ConclusionIn the first mega-analysis of fMRI studies of executive function in OCD, we found strong evidence of weaker frontoparietal activation during executive control tasks. Our findings also suggest a failure of default mode network regions to appropriately disengage during task performance in OCD.

neuroscience↗

bioRxiv2025

The interaction of XPG with TFIIH through p62 and XPD is required for the completion of nucleotide excision repair

Nucleotide excision repair (NER) is the key pathway for the removal of DNA damage induced by UV irradiation and chemotherapeutic reagents. Protein-protein interactions are crucial for the dynamic and coordinated assembly of the proteins involved at DNA lesion. Here we focus on the role of interactions between the multi-subunit helicase/translocase complex TFIIH and the 3 endonuclease XPG. We show that XPG interacts with the p62 and XPD subunits of TFIIH through its long spacer region located in the middle of its split active site. We show the interactions between three acidic regions of XPG with the pleckstrin homology (PH) domain of p62 are of moderate importance for NER, while interactions with XPD are critical for activity. Combining mutations in the p62 and XPD interaction domains leads to additive defects in NER activity. Unexpectedly, we show that these interactions are not required for the recruitment of XPG, but rather for the formation of a catalytically competent NER complex and for triggering the incision 5 to the lesion by ERCC1-XPF. Our studies provide fundamental insights into how interactions between TFIIH and XPG contribute to the NER pathway and more generally how modular protein-protein interactions control each step along the NER reaction coordinate.

biochemistry↗

bioRxiv2024

Engineering a Cell-Based Orthogonal Ubiquitin Transfer Cascade for Profiling the Substrates of RBR E3 Parkin

The E3 ubiquitin (UB) ligase Parkin utilizes a Ring-Between-Ring (RBR) domain to mediate the transfer of UB to its substrates to regulate diverse cellular functions, including mitochondrial quality control, cell cycle progression, metabolism programming, and the establishment of synaptic functions. Mutations affecting the E3 ligase activity of Parkin are associated with cancer and Parkinsons disease (PD). An essential role of Parkin is to synthesize UB chains on the surface of damaged mitochondria to initiate mitophagy. Still, it is not clear how Parkin carries out other biological functions through the ubiquitination of its downstream targets in the cell. We hypothesized that a comprehensive substrate profile of Parkin would facilitate the discovery of ubiquitination pathways underpinning its multifaceted roles in cell regulation and reveal mechanistic linkages between Parkin malfunction and disease development. Here, we used phage display to assemble an orthogonal ubiquitin transfer (OUT) cascade of Parkin that can exclusively deliver an engineered UB mutant (xUB) to Parkin and its substrates in living cells. We then generated a substrate profile of Parkin by purifying xUB-conjugated proteins from cells and identifying them by proteomics. The OUT screen identified Parkin substrates involved in DNA replication, protein translation, intracellular protein transport, and rhythmic regulation. Based on previous literature implicating alterations in membrane vesicle trafficking in PD, we verified Parkin-catalyzed ubiquitination of Rab GTPases (Rab1a, Rab5a, Rab5c, Rab7a, Rab8a, Rab10, an Rab13) as well as CDK5, with reconstituted ubiquitination reactions in vitro and in cells. We also found chemical-induced stimulation of mitophagy enhanced Parkin-mediated ubiquitination of Rab proteins. These findings demonstrate that the OUT cascade of Parkin can serve as an empowering tool for identifying Parkin substrates to elucidate its cellular functions.

biochemistry↗

bioRxiv2024

BioLP-bench: Measuring understanding of AI models of biological lab protocols

Language models rapidly become more capable in many domains, including biology. Both AI developers and policy makers [1] [2] [3] are in need of benchmarks that evaluate their proficiency in conducting biological research. However, there are only a handful of such benchmarks[4, 5], and all of them have their limitations. This paper introduces the Biological Lab Protocol benchmark (BioLP-bench) that evaluates the ability of language models to find and correct mistakes in a diverse set of laboratory protocols commonly used in biological research. To evaluate understanding of the protocols by AI models, we introduced in these protocols numerous mistakes that would still allow them to function correctly. After that we introduced in each protocol a single mistake that would cause it to fail. We then presented these modified protocols to an LLM, prompting it to identify the mistake that would cause it to fail, and measured the accuracy of a model in identifying such mistakes across many test cases. Only OpenAI o1-preview scored similarly to the performance of human experts, while other language models demonstrated substantially worse performance, and in most cases couldnt correctly identify the mistake. Code and dataset are published at https://github.com/baceolus/BioLP-bench

bioinformatics↗

bioRxiv2023

Single-nucleus transcriptomics of epicardial adipose tissue from females reveals exercise control of innate and adaptive immune cells

Coronary artery disease (CAD) is a leading cause of death in women. Although exercise mitigates CAD, the mechanisms by which exercise impacts epicardial adipose tissue (EAT) are unknown. We hypothesized that exercise promotes an anti-inflammatory microenvironment in EAT from female pigs. Yucatan pigs (n=7) were assigned to sedentary (Sed) or exercise (Ex) treatments and coronary arteries were occluded (O) with an ameroid to mimic CAD or remained non-occluded (N). EAT was collected for bulk and single nucleus transcriptomic sequencing (snRNA-seq). Exercise upregulated G-protein coupled receptor, S100 family, and FAK pathways and downregulated the coagulation pathway. Exercise increased the interaction between immune, endothelial, and mesenchymal cells in the insulin-like growth factor pathway and between endothelial and other cell types in the platelet endothelial cell adhesion molecule 1 pathway. Sub- clustering revealed nine cell types in EAT with fibroblast and macrophage populations predominant in O-Ex EAT and T cell population predominant in N-Ex EAT. Coronary occlusion impacted the largest number of genes in T and endothelial cells. Genes related to fatty acid metabolism were the most highly upregulated in non-immune cells from O-Ex EAT. Sub-clustering of endothelial cells revealed that N-Ex EAT separated from other treatments. In conclusion, aerobic exercise increased interaction amongst immune and mesenchymal and endothelial cells in female EAT. Exercise was minimally effective at reversing alterations in gene expression in endothelial and mesenchymal cells in EAT surrounding occluded arteries. These findings lay the foundation for future work focused on the impact of exercise on cell types in EAT. Significance StatementCoronary artery disease (CAD) is a leading cause of death in women. However, the role of epicardial adipose tissue (EAT) in the development of CAD in females and how exercise, which is recommended to slow CAD progression, impacts EAT are unknown. The effect of aerobic exercise on gene expression in EAT was investigated with RNA-sequencing, revealing significant alterations in fatty acid processing and immunoregulatory processes. This study provides valuable insights into the molecular and cellular changes induced in EAT by exercise in the context of chronic ischemic heart disease in females. These findings bolster current understanding of the impact of aerobic exercise on cardiac health in females and provide a foundation for future research in the field of exercise science.

physiology↗

bioRxiv2020

Heparin as an Anti-Inflammatory Agent

Timely control of the cytokine release syndrome (CRS) at the severe stage of COVID-19 is key to improving the treatment success and reducing the mortality rate. The inhibition of the activity of the two key cytokines, IFN{gamma} and IL-6, can significantly reduce or even reverse the development of the cytokine storm. The objective of our investigations is to reveal the anti-inflammatory potential of heparin for prevention and suppression of the development of CRS in acute COVID-19 patients. The effect of low-molecular-weight heparin (LMWH) on IFN{gamma} signalling inside the stimulated WISH cells was investigated by measuring its antiproliferative activity and the translocation of phosphorylated STAT1 in the nucleus. The mechanism of heparin binding to IFN{gamma} and IL-6 and therefore inhibition of their activity was studied by means of extensive molecular-dynamics simulations. We find that LMWH binds with high affinity to IFN{gamma} and is able to inhibit fully the interaction with its cellular receptor. It also influences the biological activity of IL-6 by binding to either IL-6 or IL-6/IL-6R thus preventing the formation of the IL-6/IL-6R/gp130 signaling complex. Our conclusion is that heparin is a potent anti-inflammatory agent that can be used in acute inflammatory conditions, due to its potential to inhibit both IFN {gamma} and IL-6 signalling pathways. Based on our results and available clinical observations, we suggest the administration of LMWH to COVID-19 patients in the initial stages of the acute phase. The beginning of the treatment and the dosage should be based on a careful follow-up of the platelet count and the D-dimer, IL-6, IFN, T-cells, and B-cells levels.

molecular biology↗

bioRxiv2019

Revealing architectural order with polarized light imaging and deep neural networks

Quantitative imaging of biological architecture with fluorescent labels is not as scalable as genomic or proteomic measurements. Here, we combine quantitative label-free imaging and deep neural networks for scalable analysis of complex structures. We reconstruct quantitative three-dimensional density, anisotropy, and orientation in live cells and tissue slices from polarization- and depth-resolved images. We report a computationally efficient variant of U-Net architecture that predicts a 3D fluorescent structure from its morphology and physical properties. We evaluate the performance of our models by predicting F-actin and nuclei in mouse kidney tissue. Further, we report label-free imaging of axon tracts and predict level of myelination in human brain tissue sections. We demonstrate the model's ability to rescue inconsistent labeling. We anticipate that the proposed approach will enable quantitative analysis of architectural order across scales of organelles to tissues.

biophysics↗

bioRxiv2018

Bayesian Classification of Microbial Communities Based on 16S rRNA Metagenomic Data

We propose a Bayesian method for the classification of 16S rRNA metagenomic profiles of bacterial abundance, by introducing a Poisson-Dirichlet-Multinomial hierarchical model for the sequencing data, constructing a prior distribution from sample data, calculating the posterior distribution in closed form; and deriving an Optimal Bayesian Classifier (OBC). The proposed algorithm is compared to state-of-the-art classification methods for 16S rRNA metagenomic data, including Random Forests and the phylogeny-based Metaphyl algorithm, for varying sample size, classification difficulty, and dimensionality (number of OTUs), using both synthetic and real metagenomic data sets. The results demonstrate that the proposed OBC method, with either noninformative or constructed priors, is competitive or superior to the other methods. In particular, in the case where the ratio of sample size to dimensionality is small, it was observed that the proposed method can vastly outperform the others.\n\nAuthor summaryRecent studies have highlighted the interplay between host genetics, gut microbes, and colorectal tumor initiation/progression. The characterization of microbial communities using metagenomic profiling has therefore received renewed interest. In this paper, we propose a method for classification, i.e., prediction of different outcomes, based on 16S rRNA metagenomic data. The proposed method employs a Bayesian approach, which is suitable for data sets with small ration of number of available instances to the dimensionality. Results using both synthetic and real metagenomic data show that the proposed method can outperform other state-of-the-art metagenomic classification algorithms.

bioinformatics↗