Biology subjects

Özdemir, E.

Publications and source records attributed to Özdemir, E..

5 recordsLinked to original sources

bioRxiv2025

Expanding the iModulon Knowledgebase for Bacillus subtilis: Updated Transcriptome Decomposition Reveals Novel Regulatory Mechanisms

1.The Gram-positive bacterium Bacillus subtilis is widely used as a model organism for studying cell differentiation, microbial physiology and gene regulation. Its genetic accessibility and strong protein secretion machinery make it an excellent host for industrial protein production. Transcriptomics has become an essential tool in understanding these traits and the organisms response to environmental stimuli. Recent advantages in transcriptomics have enabled genome-wide analysis of gene expression patterns under various environmental conditions and genetic perturbations, interpreting such data, however, remains challenging. Independent Component Analysis (ICA) has emerged as a powerful method to decompose bacterial transcriptomes into sets of co-regulated genes - so-called iModulons. In this study, we present an updated iModulon decomposition of Bacillus subtilis transcriptomes, generated from a compendium of 782 high-quality RNAseq samples. This dataset includes a wide range of environmental and genetic conditions. ICA decomposition revealed 142 iModulons, that captured 80% of the expression variance. We compare our version of the modularized B. subtilis transcriptome with previous decompositions and show that the updated composition enhances our understanding of B. subtilis gene regulation and enables novel insights into the organisms regulon structure and gene memberships of the WalR regulon.

systems biology↗

bioRxiv2024

A synthetic platform for multiplex screening of cell-cell communication between soil fungi

Fungi are essential members across ecosystems, yet phytopathogenic fungi pose an increasing risk to crop yields. Despite their ecologic importance, cell-cell communication in fungi is underexplored, partly due to the lack of high-throughput techniques. Here we developed a Yeast Mating Platform (YeMaP) to investigate the interaction between fungal G protein-coupled receptors (GPCRs) and pheromone peptides. We used YeMaP for high- throughput screening of 8,000 pheromone sequences and identified new peptides with improved agonism or antagonism action. We found that these peptides can be applied in a native fungal system such as the plant pathogen Fusarium oxysporum, to control hyphal chemotropism and reduce plant root penetration. Additionally, we utilized YeMaP in a one- pot assay to investigate how abiotic factors influence the communication of multiple pheromone-GPCR combinations and found that the cell-cell communication mediated by the GPCR Ste2 from F. oxysporum signalled robustly across different abiotic factors, while other fungal GPCR-pheromone interactions were more sensitive to changes. Taken together, YeMaP accelerates the identification of fungal GPCR-peptide interactions by enabling one- pot assays, and serves as model system for studying fungal cell-cell communication.

synthetic biology↗

bioRxiv2024

Machine Learning Uncovers the Transcriptional Regulatory Network for the Production Host Streptomyces albidoflavus J1074

Streptomyces albidoflavus is a popular and genetically tractable platform strain used for natural product discovery and production via the expression of heterologous biosynthetic gene clusters (BGCs). However, its transcriptional regulatory network (TRN) and its impact on secondary metabolism is poorly understood. Here we characterized its TRN by applying an independent component analysis to a compendium of 218 high quality RNA-seq transcriptomes from both in-house and public sources spanning 88 unique growth conditions. We obtained 78 independently modulated sets of genes (iModulons) that quantitatively describe the TRN and its activity state across diverse conditions. Through analyses of condition-dependent TRN activity states, we (i) describe how the TRN adapts to different growth conditions, (ii) conduct a cross-species iModulon comparison, uncovering shared features and unique characteristics of the TRN across lineages, (iii) detail the transcriptional activation of several endogenous BGCs, including surugamide, minimycin and paulomycin, and (iv) infer potential functions of 40% of the uncharacterized genes in the S. albidoflavus genome. Our findings provide a comprehensive and quantitative understanding of the TRN of S. albidoflavus, providing a knowledge base for further exploration and experimental validation. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=198 SRC="FIGDIR/small/574332v3_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@1a7d0aorg.highwire.dtl.DTLVardef@10750eborg.highwire.dtl.DTLVardef@1518644org.highwire.dtl.DTLVardef@145f5b4_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2019

A metabolic reconstruction of Lactobacillus reuteri JCM 1112 and analysis of its potential as a cell factory

BackgroundLactobacillus reuteri is a heterofermentative Lactic Acid Bacterium (LAB) that is commonly used for food fermentations and probiotic purposes. Due to its robust properties, it is also increasingly considered for use as a cell factory. It produces several industrially important compounds such as 1,3-propanediol and reuterin natively, but for cell factory purposes, developing improved strategies for engineering and fermentation optimization is crucial. Genome-scale metabolic models can be highly beneficial in guiding rational metabolic engineering. Reconstructing a reliable and a quantitatively accurate metabolic model requires extensive manual curation and incorporation of experimental data.\n\nResultsA genome-scale metabolic model of L. reuteri JCM 1112T was reconstructed and the resulting model, Lreuteri_530, was validated and tested with experimental data. Several knowledge gaps in the metabolism were identified and resolved during this process, including presence/absence of glycolytic genes. Flux distribution between the two glycolytic pathways, the phosphoketolase and Embden-Meyerhof-Parnas pathways, varies considerably between LAB species and strains. As these pathways result in different energy yields, it is important to include strain-specific utilization of these pathways in the model. We determined experimentally that the Embden-Meyerhof-Parnas pathway carried at most 7% of the total glycolytic flux. Predicted growth rates from Lreuteri_530 were in good agreement with experimentally determined values. To further validate the prediction accuracy of Lreuteri_530, the predicted effects of glycerol addition and adhE gene knock-out, which results in impaired ethanol production, were compared to in vivo data. Examination of both growth rates and uptake- and secretion rates of the main metabolites in central metabolism demonstrated that the model was able to accurately predict the experimentally observed effects. Lastly, the potential of L. reuteri as a cell factory was investigated, resulting in a number of general metabolic engineering strategies.\n\nConclusionWe have constructed a manually curated genome-scale metabolic model of L. reuteri JCM 1112T that has been experimentally parameterized and validated and can accurately predict metabolic behavior of this important platform cell factory.

systems biology↗

bioRxiv2019

Adaptive laboratory evolution reveals general and specific chemical tolerance mechanisms and enhances biochemical production

Tolerance to high product concentrations is a major barrier to achieving economically viable processes for bio-based chemical production. Chemical tolerance mechanisms are often unknown, thus their rational design is not achievable. To reveal unknown tolerance mechanisms we used an automated platform to evolve Escherichia coli to grow in previously toxic concentrations of 11 chemicals that have applications as polymer precursors, chemical intermediates, or biofuels. Re-sequencing of isolates from 88 independently evolved populations, reconstruction of mutations, and cross-compound tolerance profiling was employed to uncover general and specific tolerance mechanisms. We found that: 1) the broad tolerance of strains towards chemicals varied significantly depending on the chemical stress condition under which the strain was evolved; 2) the strains that acquired high levels of NaCl tolerance also became broadly tolerant to most chemicals; 3) genetic tolerance mechanisms included alterations in regulatory, cell wall, transcriptional and translational functions, as well as more chemical-specific mechanisms related to transport and metabolism; 4) using pre-tolerized starting strains can significantly enhance subsequent production of chemicals when a production pathway is inserted; and 5) only a subset of the evolved isolates showed improved production indicating that this approach is especially useful when a large number of independently evolved isolates are screened for production. We provide a comprehensive genotype-phenotype map based on identified mutations and growth phenotypes for 224 chemical tolerant strains.

microbiology↗