Biology subjects

Hosseini, S.

Publications and source records attributed to Hosseini, S..

4 recordsLinked to original sources

bioRxiv2025

C3PI: Component Puzzle Protein-Protein Interaction Prediction

Proteins primarily perform their functions through interactions with other proteins, making the accurate prediction of protein-protein interactions (PPIs) a fundamental problem. Experimental methods for determining PPIs are often slow and expensive, which has driven significant efforts to improve the performance of computational methods in this field. While many methods have been designed, recent thorough investigations proved that the existing methods learn exclusively from sequence similarities and node degrees. When such data leakage is avoided, performances were shown to become random. We introduce C3PI, a novel sequence-based deep learning framework designed for predicting PPIs. C3PI uses as input ProtT5 protein embeddings into a complex architecture that includes two novel components, a puzzler and an entangler, which significantly enhance the models performance. Through extensive comparisons with state-of-the-art methods across many datasets, C3PI consistently outperforms competing approaches, especially in key metrics such as AUPRC and AUROC. Most importantly, C3PI is the first PPI prediction method to achieve a significant improvement over random on the leakage-free gold standard dataset. C3PI is available as a web server at c3pi.csd.uwo.ca and source code from github.com/lucian-ilie/C3PI.

bioinformatics↗

bioRxiv2025

Glial cells promote infection by neurotropic Influenza A viruses in vitro

Although influenza A viruses (IAV) are notorious respiratory pathogens, some IAV strains can reach and replicate in the central nervous system (CNS) in vivo. In particular, highly pathogenic avian influenza viruses (HPAIV) pose a threat for future pandemics and are linked to greater neurotropic potential. Moreover, neurotropic IAV strains have shown a more significant impact on the onset and pathogenesis of neurodegenerative diseases (NDD). However, despite its clinical relevance, the dynamics and cellular tropism of IAV infection in the CNS are not well understood. In this study, we analyzed the replication of HPAIV H7N7 in vitro using a primary murine triple co-culture system comprising neurons, astrocytes, and microglia. We found that microglia become highly infected early on and induce a strong pro-inflammatory response before undergoing apoptosis. Using fluorescence microscopy with automated single-cell profiling, we found that, in contrast to non-neurotropic H3N2, the H7N7 nucleoprotein accumulated in neuronal somata throughout the infection without being transported into dendrites or axons. A combination of single-cell and co-culture replication assays led us to conclude that astrocytes are the primary virus producers of HPAIV H7N7 in the CNS. Our results illuminate the acute phase of neurotropic IAV infection, highlighting its implications for the association between IAV and the development of neurodegenerative diseases.

microbiology↗

bioRxiv2023

Seq-InSite: sequence supersedes structure for protein interaction site prediction

Proteins accomplish cellular functions by interacting with each other, which makes the prediction of interaction sites a fundamental problem. Computational prediction of the interaction sites has been studied extensively, with the structure-based programs being the most accurate, while the sequence-based ones being much more widely applicable, as the sequences available outnumber the structures by two orders of magnitude. We provide here the first solution that achieves both goals. Our new sequence-based program, Seq-InSite, greatly surpasses the performance of sequence-based models, matching the quality of state-of-the-art structure-based predictors, thus effectively superseding the need for models requiring structure. Seq-InSite is illustrated using an analysis of four protein sequences. Seq-InSite is freely available as a web server at seq-insite.csd.uwo.ca and as free source code, including trained models and all datasets used for training and testing, at github.com/lucian-ilie/seq-insite.

bioinformatics↗

bioRxiv2021

IL-37 expression reduces acute and chronic neuroinflammation and rescues cognitive impairment in an Alzheimer s disease mouse model

The anti-inflammatory cytokine interleukin-37 (IL-37) is a member of the IL-1 family but not expressed in mice. We used a human IL-37 (hIL-37tg) expressing mouse, which has been subjected to various models of local and systemic inflammation as well as immunological challenges. Those studies demonstrate an immune-modulatory role of IL-37 which can be characterized as an important suppressor of innate immunity. We investigated the functions of IL-37 in the CNS and explored the effects of IL-37 on neuronal architecture and function, microglia phenotype, cytokine production and behavior after inflammatory challenge by intraperitoneal LPS-injection. Reduced spine density, activated microglia phenotype and impaired long-term potentiation (LTP) were observed in wild-type mice after LPS injection, whereas hIL-37tg mice showed no impairment. In addition, we crossed the hIL-37tg mouse with an animal model of Alzheimers disease (APP/PS1) to investigate the anti-inflammatory properties of IL-37 under chronic neuroinflammatory conditions. Our results show that IL-37 is able to limit inflammation in the brain after acute inflammatory events and prevent the loss of cognitive abilities in a mouse model of AD.

neuroscience↗