Biology subjects

Ramezani, A.

Publications and source records attributed to Ramezani, A..

3 recordsLinked to original sources

bioRxiv2025

In-cell Structure and Variability of Pyrenoid Rubisco

Ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) is a key enzyme in the global carbon cycle, catalyzing CO2 fixation during photosynthesis. To overcome Rubiscos inherent catalytic inefficiency, many photosynthetic organisms have evolved CO2-concentrating mechanisms. Central to these mechanisms is the pyrenoid, a protein-dense organelle within the chloroplast of eukaryotic algae, which increases the local concentration of CO2 around Rubisco and thereby enhances its catalytic efficiency. Although the structure of Rubisco has been extensively studied by in vitro methods such as X-ray crystallography and single particle cryo-EM, its native structure within the pyrenoid, its dynamics, and its association with binding partners remain elusive. Here, we investigate the structure of native pyrenoid Rubisco inside the green alga Chlamydomonas reinhardtii by applying cryo-electron tomography (cryo-ET) on cryo-focused ion beam (cryo-FIB) milled cells, followed by subtomogram averaging and 3D classification. Reconstruction at sub-nanometer resolution allowed accurate modeling and determination of a closed (activated) Rubisco conformation. Comparison to other reconstructed subsets revealed local variations at the complex active site and at the large subunit dimers interface, as well as association with binding proteins. The different structural subsets distribute stochastically within the pyrenoid. Taken together, these findings offer a comprehensive description of the structure, dynamics, and functional organization of Rubisco within the pyrenoid, providing valuable insights into its critical role in CO2 fixation.

cell biology↗

bioRxiv2025

Higher order synthetic lethals are keys to minimize cancer treatment effects on non-tumor cells

Metabolic rewiring in cancer cells facilitates the provision of essential precursors for the unbridled growth of tumors. Exploring these cancer-specific metabolic changes offers potential selective therapeutic strategies. However, targeting a single essential gene in cancer treatment often faces challenges, including resistance, lack of targetable oncogenes, and potential harm to non-tumor cells. Attacking multiple targets is hypothesized as a solution to overcome these issues, e.g., a synthetic lethal set, defined as a minimal combination of non-lethal genetic mutations leading to cell death. This study examined the potential of synthetic lethal sets to identify selective drug targets for 13 cancers and the corresponding non-tumor tissues, utilizing context-specific genome-scale metabolic models. To ensure the minimization of therapeutic side effects, this work introduced the concept of strictly-selective drug targets (SSDTs) and the harmlessness of identified targets in all 13 different non-tumor tissues was meticulously verified. Accordingly, for 13 types of cancers, over 500 SSDTs were identified, predominantly including higher-order synthetic lethal sets with more than two targets in each set. Interestingly, for specific cancers where single essential or synthetic lethal genes could not provide acceptable solutions, SSDTs were provided by higher-order synthetic lethal sets. Therefore, for the first time, this study successfully showed that leveraging higher-order synthetic lethal sets holds the key to promising strictly-selective solutions. Furthermore, nine quadruple SSDTs were identified which commonly target five different cancers without harming any of the 13 non-tumor tissues. Further experimental validation of these findings is required to select the most promising treatments for clinical studies.

systems biology↗

bioRxiv2022

A Chemical-mechanical Coupled Model Predicts Roles of Spatial Distribution of Morphogen in Maintaining Tissue Growth

The exact mechanism controlling cell growth remains a grand challenge in developmental biology and regenerative medicine. The Drosophila wing disc tissue serves as an ideal biological model to study growth regulation due to similar features observed in other developmental systems. The mechanism of growth regulation in the wing disc remains a subject of intense debate. Most existing models to study tissue growth focus on either chemical signals or mechanical forces only. Here we developed a multiscale chemical-mechanical coupled model to test a growth regulation mechanism depending on the spatial range of the morphogen gradient. By comparing the spatial distribution of cell division and the overall shape of tissue obtained in the coupled model with experimental data, our results show that the distribution of the Dpp morphogen can be critical in resulting tissue size and shape. A larger tissue size with a faster growth rate and more symmetric shape can be achieved if the Dpp gradient spreads in a larger domain. Together with the absorbing boundary conditions, the feedback regulation that downregulates Dpp receptors on the cell membrane allows the further spread of the morphogen away from its source region, resulting in prolonged tissue growth at a more spatially homogeneous growth rate. Summary StatementA multiscale chemical-mechanical model was developed by coupling submodels representing dynamics of a morphogen gradient at the tissue level, intracellular chemical signals, and mechanical properties at the subcellular level. By applying this model to study the Drosophila wing disc, it was found that the spatial range of the morphogen gradient affected tissue growth in terms of the growth rate and the overall shape.

developmental biology↗