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Papazian, A.

Publications and source records attributed to Papazian, A..

3 recordsLinked to original sources

Predicting Differential Protein-Protein Interactions

Motivation Analysis of context-specific protein-protein interactions (PPIs) provides deeper insight into protein function, revealing how cellular pathway components interact in certain perturbation conditions. However, identifying such interactions experimentally often requires combining affinity purification with mass spectrometry, proving costly and time-consuming. On the other hand, it has been shown that an increase in protein abundance does not always correspond to an increase in protein interaction, making it an unsuitable surrogate for interaction studies. Results To address this, a random forest model was created using PPI-specific MINT embeddings and condition-specific mass spectrometry protein abundance information to predict differential interactions across two experimental conditions. The model was trained and tested on validated context-specific PPIs from eight distinct cell-lines, demonstrating proficiency in predicting differential PPIs for both novel proteins and cell lines. To our knowledge, we provide the first computational model that predicts differential PPIs between experimental conditions. Availability and implementation The code is available on GitHub and backed up on Zenodo (DOI: 10.5281/zenodo.23758127). The model is freely available on Zenodo (DOI: 10.5281/zenodo.23757927).

bioinformatics↗

Stress induces DCP2 translation via a stalling-dependent mechanism

The integrated stress response (ISR) globally suppresses protein synthesis while selectively permitting translation of a small subset of stress-responsive mRNAs, many of which contain upstream or overlapping open reading frames (uORFs/oORFs). Although translational induction of transcripts such as ATF4 has classically been attributed to delayed re-initiation caused by reduced ternary complex availability, the mechanisms by which uORFs and oORFs allow ISR-selective translation remain incompletely understood. Here, using ribosome profiling during early ISR activation combined with reporter assays, we identify DCP2, encoding a major mRNA decapping enzyme, as a previously unrecognized ISR-induced transcript. We show that translational induction of DCP2 depends on an overlapping ORF whose conserved 3' region, corresponding to a ribosome pausing site, acts as a potent inhibitory element. Both the DCP2 oORF and main ORF increase in translation during stress, indicating that stress relieves repression by this inhibitory element. This reveals a mode of ISR-dependent gene regulation in which inhibition by a nascent peptide or stalling element embedded either in a uORF or an oORF is relieved upon stress to induce translation.

molecular biology↗

A cellular taxonomy of the bone marrow stroma in homeostasis and leukemia demonstrates cancer-crosstalk with stroma to impair normal tissue function

Stroma is a poorly defined non-parenchymal component of virtually every organ with key roles in organ development, homeostasis and repair. Studies of the bone marrow stroma have defined individual populations in the stem cell niche regulating hematopoietic regeneration and capable of initiating leukemia. Here, we use single-cell RNA-seq to define a cellular taxonomy of the mouse bone marrow stroma and its perturbation by malignancy. We identified seventeen stromal subsets expressing distinct hematopoietic regulatory genes, spanning new fibroblastic, and osteoblastic subpopulations. Emerging acute myeloid leukemia resulted in impaired osteogenic differentiation and reduced production of hematopoietic regulatory molecules necessary for normal hematopoiesis. Thus, cancer can affect tissue stroma in which they reside to disadvantage normal parenchymal cells. Our taxonomy of the regulatory stromal compartment provides experimental support for a model where malignant clone is not a destroyer of normal tissue but an architect of it, remodeling tissue stroma to enable emergent cancer.

cell biology↗