Biology subjects

Ozturk, M.

Publications and source records attributed to Ozturk, M..

7 recordsLinked to original sources

bioRxiv2026

Mismatch type impacts interference and priming activities in the type I-E CRISPR-Cas system

Type I-E CRISPR-Cas systems direct RNA-guided interference against foreign nucleic acids using the CRISPR RNA (crRNA)-guided Cascade complex and Cas3 helicase-nuclease. DNA targeting by Cascade-Cas3 promotes priming, a mechanism that allows for rapid acquisition of new spacers within the CRISPR array. Target mutations in the PAM and PAM-proximal seed region can block interference but may still allow priming. Previous studies have suggested that target mutations to T and A are tolerated, but that C and G substitutions are deleterious to interference and priming, respectively. However, the contributions of the crRNA spacer sequence to mutational tolerance remain unclear. Here, we systematically tested the effects of crRNA seed sequences on mutational tolerance. We engineered four E. coli strains with variable spacer sequences and tested CRISPR interference and priming against a plasmid library for each strain. Consistent with prior studies, we observe that mutations to C or G in the seed can be highly deleterious, especially at positions 1, 2 and 4. However, the corresponding crRNA sequence also strongly impacts the level of defect, with rC-dC and rA/G-dG causing the largest defects in our plasmid library experiments. Using in vitro biochemistry, we observe that mismatch type at the first position of the seed affects Cas8 conformation, and results in reduction in the rates of both Cascade-target binding and Cas3 recruitment. Overall, our results reveal that although nucleotide identity of target mutations is an important determinant of type I-E CRISPR immunity, the crRNA sequence also strongly impacts immune outcomes upon target mutation.

biochemistry↗

bioRxiv2026

Scalable high-fidelity human vascularized cortical assembloids recapitulate neurovascular co-development and cell specialization

Human cortical development involves the coupling of neurogenesis and cerebrovascular growth. However, interactions between neural and vascular cells are largely missing in most brain organoids, which are crucial models for studying neurodevelopment and disease. Here, we establish vascularized cortical assembloids (vCAs) by fusing mesoderm-derived vascular organoids (VOs) with cortical organoids (COs). vCAs self-assemble lumenized networks of endothelial cells, pericytes, and perivascular fibroblasts that acquire blood-brain barrier (BBB) specialization and arteriovenous specification in vitro. Single-cell RNA-sequencing and immunofluorescence imaging revealed that vascularization improves neuroepithelial architecture, reduces hypoxia and apoptosis, expands cortical progenitor pools, and enhances neuronal maturation and connectivity compared with COs. Moreover, atlas-level integration with human neurodevelopmental tissue and cross-protocol benchmarking demonstrate superior transcriptional concordance, especially for vascular cell and glial populations, relative to existing approaches. This scalable and reproducible platform improves fidelity and throughput for modeling human neurovascular co-development and enables systematic studies across brain regions and diseases using engineered or patient-derived iPSCs.

developmental biology↗

bioRxiv2025

Protein Kinase C δ: a critical hub regulating macrophage immunomodulatory functions during Mycobacterium tuberculosis infection

A host-modulating candidate gene involved in putative pathogen-killing pathways, with potential novel therapeutic intervention, Protein Kinase C - {delta} (PKC{delta}) has been recognized as a critical marker of inflammation with clinical and experimental evidence in recent years. Pulmonary microenvironment during Mtb infection is largely governed by lung resident macrophages, initiating innate and subsequent adaptive immune responses. We investigated the role of PKC{delta} in macrophages using a macrophage-specific PKC{delta} knockout mice model (LysMcrePKC{delta}flox/flox). PKC{delta} deficiency in macrophages triggers an early lymphocytic immune response, increases neutrophil recruitment, and reduces inflammatory macrophages in the lungs, leading to higher Mtb burden and exacerbated pathology. Experimental and omics analysis further revealed that dysregulation of antimicrobial effector functions is detrimental to macrophages ability to restrict bacterial growth in vitro. Importantly this defect was mitigated by exogenous GM-CSF supplementation and/or overexpressing PKC{delta} in macrophages. Thus, PKC{delta} plays a crucial role in immune modulation during Mtb infection with GM-CSF amongst several downstream pathways through which PKC{delta} exerts its regulatory effects. TeaserPKC{delta} is crucial for immune modulation during Mtb infection revealing macrophages as a potential axis of signaling.

immunology↗

bioRxiv2024

Characterization of a novel neurodevelopmental rare disease caused by a mutation within the autophagy gene ATG9B

Autophagy is a highly conserved eukaryotic cellular process whose dysfunction results in human pathologies including cancer and neurodegenerative disease. First identified in yeast, ATG genes are central players in autophagy. Although their roles in cancer and neurodegenerative disease are well known, Mendelian diseases associated with ATG genes are rare. Mutations in core autophagy genes ATG5 and ATG7 have been previously reported to cause rare genetic disorders with autosomal recessive inheritance pattern. Here we report, for the first time, a rare genetic disorder that results from a deletion/frameshift mutation in human ATG9B, the placenta specific homologue of yeast ATG9 in humans. The 11-nucleotide deletion causes a frameshift and addition of a premature stop codon, truncating the C-terminal cytosolic domain of the ATG9B protein. The pediatric patients carrying the mutant allele homozygous were children of a consanguineous marriage and displayed neurodevelopmental anomalies including mental retardation. We hypothesized that this phenotype originates during placental development. To characterize the effects of the mutation and gain insight on the specific functions of ATG9B in a physiological setting, we used mammalian cells and generated a knock-in mouse model. Truncated ATG9B was not stable when expressed in cells. It was localized to perinuclear vesicles like the WT protein, but not to peripheral vesicles. Homozygous knock-in mice were viable, fertile and displayed no gross phenotypical abnormalities. Histomorphometry analysis of the placenta layers did not reveal a significant difference between mutant and control embryos. The assessments of neurobehavioral tests were similar in wild-type and homozygous knock-in mice. However, knock-in mice had a reduced fear memory trend, which is an amygdala-involved response.

genetics↗

bioRxiv2021

Knowledge graph analytics platform with LINCS and IDG for Parkinson's disease target illumination

BackgroundLINCS, "Library of Integrated Network-based Cellular Signatures", and IDG, "Illuminating the Druggable Genome", are both NIH projects and consortia that have generated rich datasets for the study of the molecular basis of human health and disease. LINCS L1000 expression signatures provide unbiased systems/omics experimental evidence. IDG provides compiled and curated knowledge for illumination and prioritization of novel drug target hypotheses. Together, these resources can support a powerful new approach to identifying novel drug targets for complex diseases, such as Parkinsons disease (PD), which continues to inflict severe harm on human health, and resist traditional research approaches. ResultsIntegrating LINCS and IDG, we built the Knowledge Graph Analytics Platform (KGAP) to support an important use case: identification and prioritization of drug target hypotheses for associated diseases. The KGAP approach includes strong semantics interpretable by domain scientists and a robust, high performance implementation of a graph database and related analytical methods. Illustrating the value of our approach, we investigated results from queries relevant to PD. Approved PD drug indications from IDGs resource DrugCentral were used as starting points for evidence paths exploring chemogenomic space via LINCS expression signatures for associated genes, evaluated as target hypotheses by integration with IDG. The KG-analytic scoring function was validated against a gold standard dataset of genes associated with PD as elucidated, published mechanism-of-action drug targets, also from DrugCentral. IDGs resource TIN-X was used to rank and filter KGAP results for novel PD targets, and one, SYNGR3 (Synaptogyrin-3), was manually investigated further as a case study and plausible new drug target for PD. ConclusionsThe synergy of LINCS and IDG, via KG methods, empowers graph analytics methods for the investigation of the molecular basis of complex diseases, and specifically for identification and prioritization of novel drug targets. The KGAP approach enables downstream applications via integration with resources similarly aligned with modern KG methodology. The generality of the approach indicates that KGAP is applicable to many disease areas, in addition to PD, the focus of this paper.

bioinformatics↗

bioRxiv2019

Unsupervised Clustering Reveals Spatially Varying Single Neuronal Firing Patterns in the Subthalamic Nucleus of Patients with Parkinson's Disease

IntroductionSubthalamic nucleus (STN) is an effective target for deep brain stimulation (DBS) to reduce the motor symptoms of Parkinsons disease (PD). It is important to identify firing patterns within the structure for a better understanding of the electro-pathophysiology of the disease. Using recently established metrics, our study aims to autonomously identify the discharge patterns of individual cells and examine their spatial distribution within the STN. MethodsWe recorded single unit activity (SUA) from 12 awake PD patients undergoing a standard clinical DBS surgery. Three extracted features from raw SUA (local variation, bursting index and prominence of peak) were used with k-means clustering to achieve the aforementioned unsupervised grouping of firing patterns. Results279 neurons were isolated and four distinct firing patterns were identified across patients: tonic (11%), irregular (55%), periodic (9%) and non-periodic bursts (25%). The mean firing rates for irregular discharges were significantly lower (p<0.05) than the rest. Tonic firings were significantly ventral (p<0.05) while periodic (p<0.05) and non-periodic (p<0.01) bursts were dorsal. The percentage of periodically bursting neurons in dorsal region and entire STN were significantly correlated with off state UPDRS tremor scores (r=0.51, p=0.04) and improvement in bradykinesia and rigidity (r=0.57, p=0.02) respectively. ConclusionStrengthening the application of unsupervised clustering for firing patterns of individual cells, this study shows a unique spatial affinity of tonic activity towards the ventral and bursting activity towards the dorsal region of STN in PD patients. This spatial preference, together with the correlation of clinical scores, can provide a clue towards understanding Parkinsonian symptom generation.

neuroscience↗

bioRxiv2018

Quantifying the effects of head movement on magnetic resonance spectroscopy estimates of gamma-aminobutyric acid

There has been keen interest in measuring in vivo GABA. However, GABA signal is low and typically measured using techniques vulnerable to the confounding effects of in-scanner head movement. This issue is particularly problematic for clinical studies since it may lead to Type I or II error in testing for group differences. While solutions to mitigate the effects of movement have been proposed, fundamental and largely unexamined issues are the nature and scale of this effect. We developed a method to quantify and characterize head movement during GABA spectroscopy and found that two parameters of movement, displacement and instantaneous movement, were inversely correlated with and accounted for 12.1% and 20.2% variance of GABA estimates respectively. We conclude that head movement can significantly affect GABA measurements and the application of methods to account for movement may improve of GABA measurement accuracy and the detection of true group differences in clinical studies.

neuroscience↗