Biology subjects

Aydin, Z.

Publications and source records attributed to Aydin, Z..

4 recordsLinked to original sources

bioRxiv2023

Structural Coverage of the Human Interactome

Complex biological processes in cells are embedded in the interactome, representing the complete set of protein-protein interactions. Mapping and analyzing the protein structures are essential to fully comprehending these processes molecular details. Therefore, knowing the structural coverage of the interactome is essential to show the current limitations. Structural modeling of protein-protein interactions requires accurate protein structures. In this study, we mapped all experimental structures to the reference human proteome. Later, we found the enrichment in structural coverage when complementary methods such as homology modeling and deep learning (AlphaFold) are included. We then collected the interactions from the literature and databases to form the reference human interactome resulting in 117,897 non-redundant interactions. When we analyzed the structural coverage of the interactome, we found that the number of experimentally determined protein complex structures is scarce, corresponding to 3.95% of all binary interactions. We also analyzed known and modeled structures to potentially construct the structural interactome with a docking method. Our analysis showed that 12.97% of the interactions from HuRI, 73.62%, and 32.94% from the filtered versions of STRING and HIPPIE could potentially be modeled with a high structural coverage or accuracy, respectively. Overall, this paper provides an overview of the current state of structural coverage of the human proteome and interactome. Significance StatementWe gathered binary protein-protein interactions from three prominent interactome databases to create a comprehensive human reference interactome. We quantified the structural coverage of the human interactome using already available structural data from four different sources. We further evaluate the percentage of interactions that can be accurately predicted using docking methods.

bioinformatics↗

bioRxiv2021

Epithelial cells of the intestine acquire cell-intrinsic inflammation signatures during ageing

During ageing, cell-intrinsic and extrinsic factors lead to the decline of tissue function and organismal health. Disentangling these factors is important for developing effective strategies to prolong organismal healthspan. Here, we addressed this question in the mouse intestinal epithelium, which forms a dynamic interface with its microenvironment and receives extrinsic signals affecting its homeostasis and tissue ageing. We systematically compared transcriptional profiles of young and aged epithelial cells in vivo and ex vivo in cultured intestinal organoids. We found that all cell types of the aged epithelium exhibit an inflammation phenotype, which is marked by MHC class II upregulation and most pronounced in enterocytes. This was accompanied by elevated levels of the immune tolerance markers PD-1 and PD-L1 in the aged tissue microenvironment, indicating dysregulation of immunological homeostasis. Intestinal organoids from aged mice still showed an inflammation signature after weeks in culture, which was concurrent with increased chromatin accessibility of inflammation-associated loci. Our results reveal a cell-intrinsic, persistent inflammation phenotype in aged epithelial cells, which might contribute to systemic inflammation observed during ageing.

genomics↗

bioRxiv2018

Widespread inter-individual gene expression variability in Arabidopsis thaliana

A fundamental question in biology is how gene expression is regulated to give rise to a phenotype. However, transcriptional variability is rarely considered and could influence the relationship between genotype and phenotype. It is known in unicellular organisms that gene expression is often noisy rather than uniform and this has been proposed to be beneficial when environmental conditions are unpredictable. However, little is known about transcriptional variability in plants. Using transcriptomic approaches, we analysed gene expression variability between individual Arabidopsis thaliana plants growing in identical conditions over a 24 hour time-course. We identified hundreds of genes that exhibit high inter-individual variability and found that many are involved in environmental responses. We also identified factors that might facilitate gene expression variability, such as gene length, the number of transcription factors regulating the genes and the chromatin environment. These results shed new light on the impact of transcriptional variability in gene expression regulation in plants.

plant biology↗

bioRxiv2018

A crowdsourced analysis to identify ab initio molecular signatures predictive of susceptibility to viral infection

Respiratory viruses are highly infectious; however, the variation of individuals physiologic responses to viral exposure is poorly understood. Most studies examining molecular predictors of response focus on late stage predictors, typically near the time of peak symptoms. To determine whether pre- or early post-exposure factors could predict response, we conducted a community-based analysis to identify predictors of resilience or susceptibility to several respiratory viruses (H1N1, H3N2, Rhinovirus, and RSV) using peripheral blood gene expression profiles collected from healthy subjects prior to viral exposure, as well as up to 24 hours following exposure. This analysis revealed that it is possible to construct models predictive of symptoms using profiles even prior to viral exposure. Analysis of predictive gene features revealed little overlap among models; however, in aggregate, these genes were enriched for common pathways. Heme Metabolism, the most significantly enriched pathway, was associated with higher risk of developing symptoms following viral exposure.

immunology↗