Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Article Citation - WoS: 6Citation - Scopus: 7Diaph1-Deficiency Is Associated With Major T, Nk and Ilc Defects in Humans(Springer/plenum Publishers, 2024) Azizoglu, Zehra Busra; Babayeva, Royala; Haskologlu, Zehra Sule; Acar, Mustafa Burak; Ayaz-Guner, Serife; Okus, Fatma Zehra; Eken, AhmetLoss of function mutations in Diaphanous related formin 1 (DIAPH1) are associated with seizures, cortical blindness, and microcephaly syndrome (SCBMS) and are recently linked to combined immunodeficiency. However, the extent of defects in T and innate lymphoid cells (ILCs) remain unexplored. Herein, we characterized the primary T, natural killer (NK) and helper ILCs of six patients carrying two novel loss of function mutation in DIAPH1 and Jurkat cells after DIAPH1 knockdown. Mutations were identified by whole exome sequencing. T-cell immunophenotyping, proliferation, migration, cytokine signaling, survival, and NK cell cytotoxicity were studied via flow cytometry-based assays, confocal microscopy, and real-time qPCR. CD4+ T cell proteome was analyzed by mass spectrometry. p.R351* and p.R322*variants led to a significant reduction in the DIAPH1 mRNA and protein levels. DIAPH1-deficient T cells showed proliferation, activation, as well as TCR-mediated signaling defects. DIAPH1-deficient PBMCs also displayed impaired transwell migration, defective STAT5 phosphorylation in response to IL-2, IL-7 and IL-15. In vitro generation/expansion of Treg cells from na & iuml;ve T cells was significantly reduced. shRNA-mediated silencing of DIAPH1 in Jurkat cells reduced DIAPH1 protein level and inhibited T cell proliferation and IL-2/STAT5 axis. Additionally, NK cells from patients had diminished cytotoxic activity, function and IL-2/STAT5 axis. Lastly, DIAPH1-deficient patients' peripheral blood contained dramatically reduced numbers of all helper ILC subsets. DIAPH1 deficiency results in major functional defects in T, NK cells and helper ILCs underlining the critical role of formin DIAPH1 in the biology of those cell subsets.Graphical AbstractThe summary of findings are presented as a graphical abstract. DIAPH1 deficiency results in multiple defects in CD4+ T, Treg, NK cells and ILCs.Article Citation - WoS: 9Citation - Scopus: 11Mesenchymal Stem Cells From Adipose Tissue Prone To Lose Their Stemness Associated Markers in Obesity Related Stress Conditions(Nature Portfolio, 2024) Al-Sammarraie, Sura Hilal Ahmed; Ayaz-Guner, Serife; Acar, Mustafa Burak; Simsek, Ahmet; Siniksaran, Betuel Seyhan; Bozalan, Habibe Damla; Ozcan, ServetObesity is a health problem characterized by large expansion of adipose tissue. During this expansion, genotoxic stressors can be accumulated and negatively affect the mesenchymal stem cells (MSCs) of adipose tissue. Due to the oxidative stress generated by these genotoxic stressors, senescence phenotype might be observed in adipose tissue MSCs. Senescent MSCs lose their proliferations and differentiation properties and secrete senescence-associated molecules to their niche thus triggering senescence for the rest of the tissue. Accumulation of senescent cells in adipose tissue results in decreased tissue regeneration and functional impairment not only in the close vicinity but also in the other tissues. Here we hypothesized that declined tissue regeneration might be associated with loss of stemness markers in MSCs population. We analyzed the expression of several stemness-associated genes of in vitro cultured MSCs originated from adipose tissue of high-fat diet and normal diet mice models. Since the heterogenous MSCs population covers a small percentage of the pluripotent stem cells, which have roles in proliferation and tissue regeneration, we measured the percentage of these cells via TRA-1-60 pluripotent state antigen. Additionally, by conducting a shotgun proteomic approach using LC-MS/MS, whole cell proteome of the adipose tissue MSCs of high-fat diet and normal diet mice were analyzed and identified proteins were evaluated via gene ontology and PPI network analysis. MSCs of obese mice showed senescent phenotype and altered cell cycle distribution due to a hostile environment with oxidative stress in adipose tissue where they reside. Additionally, the number of pluripotent markers expressing cells declined in the MSC population of the high-fat diet mice. Gene expression analysis evidenced the loss of stemness with a decrease in the expression of stemness-associated genes. Of the proteomic comparison of the normal and the high-fat diet group, MSCs revealed that stemness-associated molecules were decreased while inflammation and senescence-associated phenotypes emerged in obese mice MSCs. Our results showed us that the MSCs of adipose tissue may lose their stemness properties due to obesity-associated stress conditions.Article Citation - WoS: 6Citation - Scopus: 7Improved Senescent Cell Segmentation on Bright-Field Microscopy Images Exploiting Representation Level Contrastive Learning(Wiley, 2024) Celebi, Fatma; Boyvat, Dudu; Ayaz-Guner, Serife; Tasdemir, Kasim; Icoz, KutayMesenchymal stem cells (MSCs) are stromal cells which have multi-lineage differentiation and self-renewal potentials. Accurate estimation of total number of senescent cells in MSCs is crucial for clinical applications. Traditional manual cell counting using an optical bright-field microscope is time-consuming and needs an expert operator. In this study, the senescence cells were segmented and counted automatically by deep learning algorithms. However, well-performing deep learning algorithms require large numbers of labeled datasets. The manual labeling is time consuming and needs an expert. This makes deep learning-based automated counting process impractically expensive. To address this challenge, self-supervised learning based approach was implemented. The approach incorporates representation level contrastive learning component into the instance segmentation algorithm for efficient senescent cell segmentation with limited labeled data. Test results showed that the proposed model improves mean average precision and mean average recall of downstream segmentation task by 8.3% and 3.4% compared to original segmentation model.