Biology subjects

Khosravi, S.

Publications and source records attributed to Khosravi, S..

7 recordsLinked to original sources

bioRxiv2026

Granger Sensori-Behavioral Taxonomy of Neuronal Ensemble Activity from Two-Photon Calcium Imaging Data

Understanding how neuronal populations interact to encode and transform sensory information is a fundamental challenge in computational neuroscience. Most existing studies, however, study neural encoding, behavioral readout, and functional connectivity as disjoint problems. Two-photon calcium imaging enables simultaneous recording of large neuronal ensembles in vivo, driven by diverse stimuli and eliciting distinct behaviors. However, extracting directional functional connectivity metrics as well as encoding and readout properties of neurons from such data remains difficult due to indirect and noisy observations of spiking activity, slow temporal dynamics, and the latent interplay between external stimuli and endogenous neural processes. Here, we introduce a unified conceptual and operational modeling and inference framework for directly extracting functional Granger causal (GC) effects between neurons, from external stimuli to neurons, and from neurons to behavior, from two-photon imaging data, in the sense of Granger. Inspired by the intersection information framework, we also identify neurons that encode features of sensory stimuli that inform behavioral readout. The resulting GC networks together with the taxonomy of functional sensori-behavioral relevance, which we call G-taxonomy, provides a powerful statistical analysis framework, enabled by the integration of several techniques including state-space modeling and inference, variational inference, and point processes. We applied the proposed framework to simulated and experimentally-recorded two-photon imaging from the mouse auditory cortex (A1) during both passive listening and active tone discrimination. Our simulation studies reveal significant improvement of our proposed methodology over existing techniques. Analysis of experimental data from the mouse A1 identifies distinct groups of cells with diverse sensori-behavioral relevance, as well as changes in functional connectivity associated with correct vs. incorrect behavior. In summary, this work provides a principled and data-driven methodology for uncovering directional interactions among the neurons, sensory stimuli, and behavior, all within the same statistical framework, offering new insights into how distributed cortical populations transform sensory inputs into behaviorally relevant representations. Author SummaryThe brain processes sensory inputs through the coordinated activity of large networks of neurons and produces readouts that elicit behavior. Understanding how information flows and is processed through these networks is a central goal of neuroscience. In this study, we present a new computational framework that identifies directional interactions among neurons in an ensemble as well as from sensory stimuli to neurons and from neurons to behavior. Utilizing the Granger formalism to identify directional effects, as opposed to common correlational measures, our framework extracts said effects directly from two-photon calcium imaging data. We tested our proposed method on both simulated data and recordings from the auditory cortex of mice during passive listening and active tone discrimination tasks. Our method revealed diverse groups of neurons in the auditory cortex with distinct functional roles and relevance to sensori-behavioral integration. Our framework provides a new way to study the flow of information in the brain and can be broadly applied to uncover neural computations across sensory and cognitive systems.

neuroscience↗

bioRxiv2024

Machine Learning Approaches for Predicting Virus-Human Protein-Protein Interactions: An Evaluation of Retroviral Interaction Networks

Virus-human protein-protein interactions (VHPPI) are key to understanding how viruses manipulate host cellular functions. This study constructed a retroviral-human PPI network by integrating multiple public databases, resulting in 1,387 interactions between 29 retroviral and 1,026 human genes. Using minimal sequence similarity, we generated a pseudo-negative dataset for model reliability. Five machine learning models--Logistic Regression (LR), Support Vector Machine (SVM), Naive Bayes (NB), Decision Tree (DT), and Random Forest (RF)--were evaluated using accuracy, sensitivity, specificity, PPV, and NPV. LR and KNN models demonstrated the strongest predictive performance, with sensitivities up to 77% and specificities of 52%. Feature importance analysis identified GC content and semantic similarity as influential predictors. Models trained on selected features showed enhanced accuracy with reduced complexity. Our approach highlights the potential of computational models for VHPPI predictions, offering valuable insights into viral-host interaction networks and guiding therapeutic target identification. SignificanceThis study addresses a crucial gap in antiviral research by focusing on the prediction of virus-host protein-protein interactions (VHPPI) for retroviruses, which are linked to serious diseases, including certain cancers and autoimmune disorders. By leveraging machine learning models, we identified essential host-pathogen interactions that underlie retroviral survival and pathogenesis. These models were optimized to predict interactions accurately, offering valuable insights into the complex mechanisms that retroviruses use to manipulate host cellular processes. Our approach highlights key host and viral proteins, such as ENV_HV1H2 and CD4, that play pivotal roles in retroviral infection and persistence. Targeting these specific interactions can potentially disrupt the viral lifecycle while minimizing toxicity to human cells. This study thus opens avenues for the development of selective therapeutic strategies, contributing to more effective and targeted antiviral interventions with fewer side effects, marking a significant step forward in computational virology and drug discovery.

bioinformatics↗

bioRxiv2024

Epigenetic state and gene expression remain stable after CRISPR/Cas-mediated chromosomal inversions

In Arabidopsis thaliana, the chromosome arms are DNA-hypomethylated and enriched in the euchromatin-specific histone mark H3K4me3. In contrast, pericentromeric regions are DNA-hypermethylated and enriched in H3K9me2. In order to investigate how chromosomal location affects epigenetic stability and gene activity, we induced two differently-sized inversions by CRISPR/Cas and introduced heterochromatic, pericentric sequences into an euchromatic chromosomal arm. The epigenetic status of the lines was investigated by whole genome bisulfite sequencing and chromatin immunoprecipitation. Additionally, we studied the effect of the chromosomal inversions on gene expression. Our analysis revealed that both inversions affected neither the global distribution of eu- and heterochromatin-specific histone marks nor the global DNA methylation landscape. However, minor epigenetic changes were found across the entire genome. Importantly, the inverted chromosome regions and their border regions did not change their epigenetic profile. The transcription analysis of both inversion lines revealed that 0.5 - 1 % of genes were differentially expressed across the entire genome. However, the expression activity of those genes encoded by the inverted segments, and located around the cutting sites of CRISPR/Cas was less affected. Thus, gene expression levels and the epigenetic landscape remain preserved following engineered chromosomal restructuring, at least in the following generations.

genetics↗

bioRxiv2024

WHIRLY1 regulates aliphatic glucosinolate biosynthesis in early seedling development of Arabidopsis

WHIRLY1 belongs to a family of plant-specific transcription factors capable of binding DNA or RNA in all three plant cell compartments that contain genetic materials. In Arabidopsis thaliana, WHIRLY1 has been studied at the later stages of plant development, including flowering and leaf senescence, as well as in biotic and abiotic stress responses. In this study, WHIRLY1 knock-out mutants of A. thaliana were prepared by CRISPR/Cas9 to investigate the role of AtWHIRLY1 during early seedling development. The loss-of-function of WHIRLY1 in 5-day-old seedlings did not cause differences in the phenotype and the photosynthetic performance of the emerging cotyledons compared to the wild type. Nevertheless, comparative RNA sequencing analysis revealed that the knock-out of WHIRLY1 affected the expression of a small but specific set of genes during this critical phase of development. About 110 genes were found to be significantly deregulated in the knockout mutant, wherein several genes involved in the early steps of aliphatic glucosinolate (aGSL) biosynthesis were suppressed compared to wild type plants. The downregulation of these genes in WHIRLY1 knock-out line led to a decreased GSL contents in seedlings and in seeds. We also examined myrosinase activity during seed-seedling transition and showed that the reduction in aGSL biosynthesis is the main reason for lowering aGSL content in young seedlings. The results suggest that AtWHIRLY1 plays a role in regulating aliphatic glucosinolate biosynthesis during early seedling development. Significance statementWHIRLY1 functions in several aspects of plant development and stress responses, however little is known about its involvement in young seedling development. Here we show that in this stage, WHIRLY1 specifically regulates expression of genes encoding enzymes in the early steps of aliphatic glucosinolate biosynthesis pathway, leading to a reduction in glucosinolate content in the WHIRLY1 knock-out seedlings.

plant biology↗

bioRxiv2022

The intra-mitochondrial contact site formed by Cqd1 and the Por1-Om14 complex modulates architecture and morphology of mitochondria

Mitochondria are essential organelles of eukaryotic cells that are characterized by their unique and complex membrane system. They are confined from the cytosol by an envelope consisting of two membranes. Signals, metabolites, proteins and lipids have to be transferred across these membranes via proteinaceous contact sites to keep mitochondria functional. In the present study we identified a novel mitochondrial contact site that is formed by the inner membrane protein Cqd1 and the outer membrane proteins Por1 and Om14. Similar to the mitochondrial porin, Por1, Cqd1 is highly conserved, suggesting that this complex is conserved in form and function from yeast to human. Cqd1 is a member of the UbiB protein kinase-like family (also called aarF domain containing kinases). It was recently shown that Cqd1 in cooperation with Cqd2 controls the cellular distribution of coenzyme Q by a yet unknown mechanism. Our data suggest that Cqd1 in addition is involved in the homeostasis of phospholipids and contributes to the maintenance of mitochondrial morphology and architecture. Summary statementHere, we show that the conserved mitochondrial inner membrane protein Cqd1 interacts with the outer membrane proteins Por1 and Om14. Additionally, we provide evidence that Cqd1 is important for maintaining mitochondrial homeostasis.

biochemistry↗

bioRxiv2020

Application of aptamers improves CRISPR-based live imaging of plant telomeres

Development of live imaging techniques for providing information how chromatin is organized in living cells is pivotal to decipher the regulation of biological processes. Here, we demonstrate the improvement of a live imaging technique based on CRISPR/Cas9. In this approach, the sgRNA scaffold is fused to RNA aptamers including MS2 and PP7. When the dead Cas9 (dCas9) is co-expressed with chimeric sgRNA, the aptamer-binding proteins fused to fluorescent protein (MCP-FP and PCP-FP) are recruited to the targeted sequence. Compared to previous work with dCas9:GFP, we show that the quality of telomere labelling was improved in transiently transformed Nicotiana benthamiana using aptamer-based CRISPR-imaging constructs. Labelling is influenced by the copy number of aptamers and less by the promoter types. The same constructs were not applicable for labelling of repeats in stably transformed plants and roots. The constant interaction of the RNP complex with its target DNA might interfere with cellular processes. HighlightAptamer-based CRISPR imaging: an opportunity for improving live-cell imaging in plants

cell biology↗

bioRxiv2017

Development of Gene-Specific Real-Time PCR Screening Method for Detection of cp4-epsps Gene in GM Crops

Among the genetically modified (GM) crops that are being approved for commercialization, herbicide resistant crops, especially those harboring cp4-epsps, have a considerable contribution. Gene-specific methods can be used to screen the presence of GMOs. To establish an effective qualitative and quantitative screening method, a set of primers were designed considering the cp4-epsps sequence. The specificity, the limit of detection, the efficiency, and the ability to quantify the GMO content were tested in GM cotton, soybean, and canola events. The results demonstrated that the primers can specifically detect cp4-epsps GM crops. The limit of detection was found to be 0.4 ng /l DNA per PCR reaction with the ability to detect 1-16 copies of the haploid genome of each GM event. The efficiency of this screening method (which was 94-110 % with an R2 higher than 0.96) indicated that these new primers can be applied to the screening of GM samples that contain the cp4-epsps gene. Also, the gene-specific real-time PCR screening method could be successfully developed for qualification of different types of GM cotton, soybean and canola events with the construction of a serial dilution ranging from 10 % to 1 %.

plant biology↗