Researcher:
Yurtseven, Ali

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Master Student

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Ali

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Yurtseven

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Yurtseven, Ali

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20221

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    Proteome analysis of the circadian clock protein PERIOD2
    (Wiley, 2022) Gül, Hüseyin; Selvi, Saba; Yılmaz, Fatma; Özçelik, Gözde; Olfaz-Aslan, Senanur; Yazan, Şeyma; Tiryaki, Büşra; Gül, Şeref; Öztürk, Nuri; N/A; Department of Chemical and Biological Engineering; Department of Molecular Biology and Genetics; Yurtseven, Ali; Kavaklı, İbrahim Halil; Master Student; Faculty Member; Faculty Member; Department of Chemical and Biological Engineering; Department of Molecular Biology and Genetics; Graduate School of Sciences and Engineering; College of Engineering; College of Sciences; N/A; 40319; 105301
    Circadian rhythms are a series of endogenous autonomous 24-h oscillations generated by the circadian clock. At the molecular level, the circadian clock is based on a transcription-translation feedback loop, in which BMAL1 and CLOCK transcription factors of the positive arm activate the expression of CRYPTOCHROME (CRY) and PERIOD (PER) genes of the negative arm as well as the circadian clock-regulated genes. There are three PER proteins, of which PER2 shows the strongest oscillation at both stability and cellular localization level. Protein-protein interactions (PPIs) or interactome of the circadian clock proteins have been investigated using classical methods such as two-dimensional gel electrophoresis, immunoprecipitation-coupled mass spectrometry, and yeast-two hybrid assay where the dynamic and weak interactions are difficult to catch. To identify the interactome of PER2 we have adopted proximity-dependent labeling with biotin and mass spectrometry-based identification of labeled proteins (BioID). In addition to known interactions with such as CRY1 and CRY2, we have identified several new PPIs for PER2 and confirmed some of them using co-immunoprecipitation technique. This study characterizes the PER2 protein interactions in depth, and it also implies that using a fast BioID method with miniTurbo or TurboID coupled to other major circadian clock proteins might uncover other interactors in the clock that have yet to be discovered.
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    Plasma proteomics identify potential severity biomarkers from COVID-19 associated network
    (Wiley-V C H Verlag Gmbh) N/A; N/A; N/A; N/A; N/A; N/A; N/A; N/A; N/A; Department of Chemical and Biological Engineering; Department of Molecular Biology and Genetics; Şahin, Ayşe Tuğçe; Yurtseven, Ali; Dadmand, Sina; Kuyucu, Gülin Özcan; Akarlar, Büşra; Küçük, Nazlı Ezgi Özkan; Şentürk, Aydanur; Ergönül, Önder; Can, Füsun; Tunçbağ, Nurcan; PhD Student; Master Student; Master Student; PhD Student; Other; Researcher; PhD Student; Faculty Member; Faculty Member; Faculty Member; Faculty Member; Department of Chemical and Biological Engineering; Department of Molecular Biology and Genetics; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; Graduate School of Health Sciences; N/A; N/A; Graduate School of Sciences and Engineering; School of Medicine; School of Medicine; College of Engineering; College of Sciences; Koç Üniversitesi İş Bankası Enfeksiyon Hastalıkları Uygulama ve Araştırma Merkezi (EHAM) / Koç University İşbank Center for Infectious Diseases (KU-IS CID); Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM); N/A; N/A; N/A; N/A; N/A; N/A; N/A; 110398; 103165; 245513; 105301
    Purpose: Coronavirus disease 2019 (COVID-19) continues to threaten public health globally. Severe acute respiratory coronavirus type 2 (SARS-CoV-2) infection-dependent alterations in the host cell signaling network may unveil potential target proteins and pathways for therapeutic strategies. In this study, we aim to define early severity biomarkers and monitor altered pathways in the course of SARS-CoV-2 infection. Experimental Design: We systematically analyzed plasma proteomes of COVID-19 patients from Turkey by using mass spectrometry. Different severity grades (moderate, severe, and critical) and periods of disease (early, inflammatory, and recovery) are monitored. Significant alterations in protein expressions are used to reconstruct the COVID-19 associated network that was further extended to connect viral and host proteins. Results: Across all COVID-19 patients, 111 differentially expressed proteins were found, of which 28 proteins were unique to our study mainly enriching in immunoglobulin production. By monitoring different severity grades and periods of disease, CLEC3B, MST1, and ITIH2 were identified as potential early predictors of COVID-19 severity. Most importantly, we extended the COVID-19 associated network with viral proteins and showed the connectedness of viral proteins with human proteins. The most connected viral protein ORF8, which has a role in immune evasion, targets many host proteins tightly connected to the deregulated human plasma proteins. Conclusions and Clinical Relevance: Plasma proteomes from critical patients are intrinsically clustered in a distinct group than severe and moderate patients. Importantly, we did not recover any grouping based on the infection period, suggesting their distinct proteome even in the recovery phase. The new potential early severity markers can be further studied for their value in the clinics to monitor COVID-19 prognosis. Beyond the list of plasma proteins, our disease-associated network unravels altered pathways, and the possible therapeutic targets in SARS-CoV-2 infection by connecting human and viral proteins. Follow-up studies on the disease associated network that we propose here will be useful to determine molecular details of viral perturbation and to address how the infection affects human physiology.