Biology subjects

Chernomoretz, A.

Publications and source records attributed to Chernomoretz, A..

8 recordsLinked to original sources

bioRxiv2026

Network organization of protein binding-site landscapes across scales

Studying protein binding sites helps explain ligand recognition and selectivity, informing drug development and repurposing. Here, we combine protein language model embeddings with network analysis to investigate how local recognition environments organize across scales. We represented 121,673 non-redundant, experimentally identified binding sites using ProtT5 embeddings of ligand-contacting residues and constructed a mutual nearest-neighbor network. Embedding proximity was associated with local structural similarity, supporting the structural relevance of network relationships. Globally, the network exhibited ligand-related organization. At the mesoscopic scale, communities revealed heterogeneous landscapes within established protein classifications, with InterPro categories ranging from compact neighborhoods to dispersed recognition environments. Focusing on kinases, a major class of drug targets, we found that communities within individual proteins distinguished separate binding regions and resolved recurrent residue-defined microenvironments within broad structural classes. Local similarities also connected sites in proteins with low sequence identity and non-overlapping InterPro annotations, suggesting shared recognition features across distant proteins. Together, these results show how network organization captures both diversification within protein categories and local similarities across their boundaries. This multiscale framework complements conventional protein classifications and provides a basis for prioritizing structural and biochemical investigations of ligand cross-reactivity, selectivity, and repurposing opportunities.

bioinformatics↗

bioRxiv2026

Cell-state mapping reveals a reversible neuroblast accumulation in the aging mouse hippocampus

Hippocampal neurogenesis supports learning and memory by generating new granule cells throughout life. However, both the rate and speed of this process decline with age. To elucidate the molecular determinants underlying the effects of aging on neuronal differentiation, we combined lineage tracing of adult-born granule cells (aGCs) with single-nucleus RNA sequencing. This approach produced a temporally resolved transcriptional atlas of aGC development. Aging led to a marked accumulation of postmitotic neuroblasts (NBs), revealing a stage-specific bottleneck in the neurogenic trajectory. Voluntary running reduced NB accumulation by restoring the progression through this developmental impasse, allowing neuronal maturation to be resumed. Notably, this effect involved a significant reduction of apoptosis at the NB stage. Together, these findings identify a reversible apoptotic checkpoint that contributes to age-related neurogenic decline and highlight postmitotic NBs as a key regulatory cell state capable of integrating pro-maturational signals to control the neurogenic output.

neuroscience↗

bioRxiv2025

Neuronal development shapes activity-dependent gene expression in a stimulus-specific manner

Neuronal activity-dependent gene expression is fundamental to a wide variety of brain functions. However, how development progress and stimulation modalities specifically affect neuron transcription is not fully understood. In this work, we first investigate the influence of development on neuronal firing and activity-driven transcription. We used an RNA sequencing approach over 7 days in vitro (DIV) or mature 21 DIV neurons, comparing neuronal depolarization with potassium chloride (KCl) versus Biccuculine application, a synaptic modality to induce neuronal activity. To further investigate how different activity patterns influence gene transcription in mature neurons, we compared global gene expression in neurons treated with three different and extensively used activation protocols: KCl, Bicuculine (Bic), and TTX withdrawal (TTXw). Our results demonstrate a strong influence of development on activity-dependent gene expression, and showed that different patterns of neuronal activity induce different transcriptional profiles and exhibit distinct temporal dynamics for the same genes. These findings offer novel insights into the complex relationship between neuronal activity and gene expression, shedding light on the context-dependent nature of activity-dependent transcriptional responses.

neuroscience↗

bioRxiv2024

Arabidopsis PRMT5 Buffers Pre-mRNA Splicing and Development Against Genetic Variation in Donor Splice Sites

Genetic variation at splice site signals significantly influences alternative splicing, leading to transcriptomic and proteomic diversity that enhances phenotypic plasticity and adaptation. However, novel splice variants can negatively impact gene expression and developmental stability. Canalization--the ability of an organism to maintain a consistent phenotype despite genetic or environmental variations--helps balance the effects of genetic variation on development and evolution. Protein arginine methyltransferase 5 (PRMT5) is a key splicing regulator in plants and animals. Most splicing changes in prmt5 mutants are linked to weak donor splice sites, suggesting that PRMT5 may buffer splicing against genetic variation. We examined PRMT5s effects on splicing and development in two genetically divergent Arabidopsis thaliana accessions with different single nucleotide polymorphisms (SNPs) affecting donor splice sites. While PRMT5 inactivation similarly affected splicing in both backgrounds, it significantly increased splicing and phenotypic differences between the accessions. Our findings suggest that PRMT5 contributes to canalization, mitigating the impact of splice site polymorphisms and facilitating the evolution of adaptive splicing patterns.

molecular biology↗

bioRxiv2023

Transcriptional dynamics orchestrating the development and integration of neurons born in the adult hippocampus

The adult hippocampus generates new granule cells (aGCs) that exhibit distinct functional capabilities along development, conveying a unique form of plasticity to the preexisting circuits. While early differentiation of adult radial glia-like neural stem cells (RGL) has been studied extensively, the molecular mechanisms guiding the maturation of postmitotic neurons remain unknown. Here, we used a precise birthdating strategy to follow newborn aGCs along differentiation using single-nuclei RNA sequencing (snRNA-seq). Transcriptional profiling revealed a continuous trajectory from RGLs to mature aGCs, with multiple sequential immature stages bearing increasing levels of effector genes supporting growth, excitability and synaptogenesis. Remarkably, four discrete cellular states were defined by the expression of distinct sets of transcription factors (TFs): quiescent neural stem cells, proliferative progenitors, postmitotic immature aGCs, and mature aGCs. The transition from immature to mature aCGs involved a transcriptional switch that shutdown molecular cascades promoting cell growth, such as the SoxC family of TFs, to activate programs controlling neuronal homeostasis. Indeed, aGCs overexpressing Sox4 or Sox11 remained stalled at the immature state. Our results unveil precise molecular mechanisms driving adult neural stem cells through the pathway of neuronal differentiation.

neuroscience↗

bioRxiv2021

Mining divergent and conserved signals in 5' splicing site sequences

The main steps of the splicing process are similar across eukaryotes. However differences in splicing factors, gene architecture and sequence divergences suggest clade-specific features of splicing and its regulation. In each organism the ensemble of 5 splicing sequences reflects the balance between natural nucleotidic variability and minimal molecular constraints to assure splicing fidelity. This compromise shapes the underlying statistical patterns in donor sequences composition. In this work we aimed to mine conserved and divergent signals in splicing donor sequences. As 5 donor sequences are a major cue for proper recognition of splicing sites we reasoned that statistical regularities of their sequence composition might reflect biological functionality and evolutionary history associated to splicing mechanisms. We considered a regularized maximum entropy modeling framework to mine for non-trivial two-site correlations in donor sequences of 30 different eukaryote organisms. Our approach allowed us to accommodate and extend within a unified framework many of the regularities observed in previous works, like the negative epistatic effects between exonic and intronic consensus sites. In addition, for each analyzed organism, we could identify minimal sets of two-site coupling patterns that could generate, at a given regularization level, observed one-site and two-site frequencies in donor sequences. Noticeably, performing a systematic and comparative analysis of 5ss we showed that lineage information could be traced from joint di-nucleotide probabilities. Specifically, we could identify characteristic two-site coupling patterns for plants and for animals and argue that they could echo differences in splicing regulation previously reported between these groups. Author summaryThe sequence composition of 5 splicing sites of eukaryote organisms reflect a complex scenario. Nucleotide variability has to coexist with the need to correctly define exon/intron boundaries and the fidelity of splicing seems to depend on a pattern of trade-offs between substitutions at different positions of the splicing site. Better understanding of these patterns may help to gain insight into the details underlying the splicing process and its evolution. In this work we aimed to study conserved and divergent signatures embedded in the sequence composition of eukaryotic 5 splicing sites. We developed generative probabilistic models that allowed us to analyze sequence composition of donor sequences for several eukaryote organisms. Our regularized models served to incrementally disentangle the minimal set of coupling parameters needed to accurately reproduced observed 1-site and 2-site nucleotide frequencies. Focusing our study on di-nucelotide probabilities we found that they actually carried phylogenetic signal. In particular, our comparative analysis allowed us to identify differential two-site coupling patterns for animal and plants that might be related to specific differences in splicing regulation.

bioinformatics↗

bioRxiv2020

ASpli2: Integrative analysis of splicing landscapesthrough RNA-Seq assays

Genome-wide analysis of alternative splicing has been a very active field of research since the early days of NGS (Next generation sequencing) technologies. Since then, ever-growing data availability and the development of increasingly sophisticated analysis methods have uncovered the complexity of the general splicing repertoire. However, independently of the considered quantification methodology, very often changes in variant concentration profiles can be hard to disentangle. In order to tackle this problem we present ASpli2, a computational suite implemented in R, that allows the identification of changes in both, annotated and novel alternative splicing events, and can deal with complex experimental designs. Our analysis workflow relies on the analysis of differential usage of subgenic features in combination with a junction-based description of local splicing changes. Analyzing simulated and real data we found that the consolidation of these signals resulted in a robust proxy of the occurrence of splicing alterations. While junction-based signals allowed us to uncover annotated as well and non-annotated events, bin-associated signals notably increased recall capabilities at a very competitive performance in terms of precision.

bioinformatics↗

bioRxiv2020

GENis, an open-source multi-tier forensic DNA information system

GENis is an open source multi-tier information system developed to run a forensic DNA database at local, regional and national levels.1 It was conceived as a highly customizable system, enforcing several security policies including: data encryption, double factor identification, structure of users roles and permissions, system-wide secure log auditing, non-repudiation protocols and a blockchain-based option to reinforce genetic profiles integrity. GENis is able to perform genetic profile queries of autosomal STRs and its design follows ENFSI2 and ISFG3 standards and recommendations. In this work, we present a summary of GENis architecture, the implemented matching rule definitions, and the Bayesian framework used to provide statistical significance of cold hits, that includes a new strategy to identify common contributors in mixture pairs.

bioinformatics↗