Biology subjects

Seker, U. O. S.

Publications and source records attributed to Seker, U. O. S..

8 recordsLinked to original sources

bioRxiv2023

A Synthetic Protein Secretion System for Living Bacterial Therapeutics

Bacteria species can thrive and colonize different parts of the human body. Those naturally residing at disease sites e.g., tumors and gut can be designed for targeted protein delivery which can provide better clinical profiles for protein-based therapies. Therefore, a generalizable, efficient, and safe protein secretion system would a be valuable tool to engineer therapeutically active microbes, especially for gram-negative species due to the presence of the second cell wall. Here, we propose an approach called iLOM-SS, an acronym for inducible Leaky Outer Membrane based Secretion System, to secrete proteins in gram-negative bacteria (GNB). In iLOM-SS, the outer membrane of GNB is made permeable by transient suppression of structural protein(s) to enable free diffusion of cargo proteins expressed at the periplasm. To validate this approach, an iLOM-SS is constructed in Escherichia coli Nissle 1917 (EcN) strain. Proteins including enzymes and a human cytokine were proven to be secreted with iLOM-SS by EcN in vitro. Further characterizations of iLOM-SS in ECN showed that fast and titratable secretion, a stop switch design for secretion, and functional implementation of the secretion system in different genetic circuit architectures were possible. We foresee that this work will pave the way for designing GNB to secrete proteins for diverse arrays of applications including but not limited to the development of sentinel cells for therapeutic purposes.

synthetic biology↗

bioRxiv2023

Highly Potent Peptide Therapeutics To Prevent Protein Aggregation In Huntington s Disease

Huntingtons disease (HD) is a progressive, autosomal dominant neurodegenerative disorder resulting from a significant amplification of CAG repeats in exon 1 of the Huntingtin (Htt) gene. More than 36 CAG repeats result in the formation of mutant Htt (mHtt) protein. These amino-terminal mHtt fragments lead to the formation of misfolded proteins, which then form aggregates in relevant brain regions. Available treatments concentrate primarily on alleviating the diseases symptoms. Therefore, therapies that can delay the progression of the disease are imperative to halt the course of the disease. Peptide-based drug therapies provide such a platform. Inhibitory peptides were screened against monomeric units of both wild type (Htt(Q25)) and mHtt fragments, including Htt(Q46)and Htt(Q103). It was accomplished by utilizing several display technologies. This study focuses on the in-vitro characterization of the screened peptides. Fibril kinetics was studied in real-time utilizing the Thioflavin T (ThT) assay. The impact of specific peptides on fibril formation was examined by observing the change in fluorescence signal. Atomic force microscopy was also used to study the influence of peptides on fibril formation. Three of the six chosen peptides (HHGANSLSLVSQD, HGLHSMHNKLTR, and WMFPSLKLLDYH) effectively inhibited aggregation. These experiments demonstrate that the chosen peptides suppress the formation of fibrils in mHtt proteins and can provide a therapeutic lead for further optimization and development.

neuroscience↗

bioRxiv2023

A Bacterial Living Therapeutics with Engineered Protein Secretion Circuits To Eliminate Breast Cancer Cells

Cancer therapy can be limited by potential side effects, and bacteria-based living cancer therapeutics have gained scientific interest in recent years. However, the full potential of bacteria as therapeutics has yet to be explored due to engineering challenges. n this study, we present a bacterial device designed to specifically target and eliminate breast cancer cells. We have engineered Escherichia coli (E. coli) to secrete a Shiga toxin, HlyE, which is a pore-forming protein that binds to HER2 receptors on breast cancer cells. This binding is facilitated by a nanobody expressed on the bacterias surface via the Ag43 autotransporter protein system. Our findings demonstrate that the nanobody efficiently binds to HER2+ cells in vitro, and we have utilized the YebF secretion system to secrete HlyE and kill the target cancer cells. Overall, our results highlight the potential of our engineered bacteria as an innovative strategy for breast cancer treatment.

synthetic biology↗

bioRxiv2023

Synergistic Screening of Peptide-Based Biotechnological Drug Candidates for Neurodegenerative Diseases using Yeast Display and Phage Display

Peptide therapeutics are robust and promising molecules for treating diverse disease conditions. These molecules can be developed from naturally occurring or mimicking native peptides, through rational design and peptide libraries. We developed a new platform for the rapid screening of the peptide therapeutics for disease targets. In the course of the study, we aimed to employ our platform to screen a new generation of peptide therapeutics candidates against aggregation prone protein targets. Two peptide drug candidates for the protein aggregation prone diseases namely Parkinsons and Alzheimers diseases were screened. Currently, there are several therapeutic applications that are only effective in masking or slowing down symptom development. Nonetheless, different approaches are developed for inhibiting amyloid aggregation in the secondary nucleation phase, which is critical for amyloid fibril formation. Instead of targeting secondary nucleated protein structures, we tried to inhibit monomeric amyloid units as a novel approach for halting disease-condition. To achieve this, we combined yeast surface display and phage display library platforms. We expressed -synuclein, amyloid {beta}40, and amyloid {beta}42 on yeast surface, and we selected peptides by using phage display library. After iterative biopanning cycles optimized for yeast cells, several peptides were selected for interaction studies. All of the peptides have been used in vitro characterization methods which are QCM-D measurement, AFM imaging, and ThT assay, and they have yielded promising results in order to block fibrillization or interact with amyloid units as a sensor molecule candidate. Therefore, peptides are good choice for diverse disease-prone molecule inhibition particularly those inhibiting fibrillization. Additionally, these selected peptides can be used as drugs and sensors to detect disease quickly and halt disease progression. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=77 SRC="FIGDIR/small/536742v1_ufig1.gif" ALT="Figure 1"> View larger version (18K): org.highwire.dtl.DTLVardef@50c81dorg.highwire.dtl.DTLVardef@181fea5org.highwire.dtl.DTLVardef@17539c7org.highwire.dtl.DTLVardef@1244a00_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2023

Learning to Generate 5' UTR Sequences for Optimized Ribosome Load and Gene Expression

The 5 untranslated region (5 UTR) of mRNA is crucial for the molecules translatability and stability, making it essential for designing synthetic biological circuits for high and stable protein expression. Several UTR sequences are patented and widely used in laboratories. This paper presents UTRGAN, a Generative Adversarial Network (GAN)-based model for generating 5 UTR sequences, coupled with an optimization procedure to ensure high expression for target gene sequences or high ribosome load and translation efficiency. The model generates sequences mimicking various properties of natural UTR sequences and optimizes them to achieve (i) up to 5-fold higher average expression on target genes, (ii) up to 2-fold higher mean ribosome load, and (iii) a 34-fold higher average translation efficiency compared to initial UTR sequences. UTRGAN-generated sequences also exhibit higher similarity to known regulatory motifs in regions such as internal ribosome entry sites, upstream open reading frames, G-quadruplexes, and Kozak and initiation start codon regions. In-vitro experiments show that the UTR sequences designed by UTRGAN result in a higher translation rate for the human TNF- protein compared to the human Beta Globin 5 UTR, a UTR with high production capacity.

bioinformatics↗

bioRxiv2021

Multiplexed Cell-Based Diagnostic Devices for Detection of Renal Biomarkers Using Genetic Circuits

The number of synthetic biology based solutions employed in the medical industry is growing every year. The whole cell biosensors being one of them, have been proven valuable tools for developing low-cost, portable, personalized medicine alternatives to conventional techniques. Based on this concept, we targeted one of the major health problems in the world, Chronic Kidney Disease (CKD). To do so, we developed two novel biosensors for the detection of two important renal biomarkers; urea and uric acid. Using advanced gene expression control strategies we improved the operational range and the response profiles of each biosensor to meet clinical specifications. We further engineered these systems to enable multiplexed detection as well as an AND-logic gate operating system. Finally, we tested the applicability of these systems and optimized their working dynamics inside complex medium human blood serum. This study could help the efforts to transition from labor-intensive and expensive laboratory techniques to widely available, portable, low cost diagnostic options.

synthetic biology↗

bioRxiv2021

Protein Engineering with A Glycosylation Circuit Enables Improved Enzyme Characteristics

Protein glycosylation is one of the most crucial and common post-translational modifications. It plays a fate-determining role and can alter many properties of proteins, making it an interesting for many biotechnology applications. The discovery of bacterial glycosylation mechanisms, opened a new perspective and transfer of C.jejuni N-linked glycosylation into laboratory work-horse E. coli increased research pace in the field exponentially. It has been previously showed that utilizing N-Linked Glycosylation, certain recombinant proteins have been furnished with improved features, such as stability and solubility. In this study, we utilized N-linked Glycosylation to glycosylate alkaline phosphatase (ALP) enzyme in E. coli and investigate the effects of glycosylation on an enzyme. Considering the glycosylation mechanism is highly dependent on the acceptor protein, ALP constructs carrying glycosylation tag at different locations of the gene has been created and glycosylation rates have been calculated. The most glycosylated construct has been selected for comparison with the native enzyme. We investigated the performance of glycosylated ALP in terms of its thermostability, proteolytic stability, tolerance to suboptimal pH and under denaturing conditions. Studies showed that glycosylated ALP performed remarkably better at optimal and harsh conditions Therefore, N-linked Glycosylation mechanism can be employed for enzyme engineering purposes and is a useful tool for industrial applications that require enzymatic activity.

synthetic biology↗

bioRxiv2020

Genetic Circuits Combined with Machine Learning Provides Fast Responding Living Sensors

Whole cell biosensors (WCBs) have become prominent in many fields from environmental analysis to biomedical diagnostics thanks to advanced genetic circuit design principles. Despite increasing demand on cost effective and easy-to-use assessment methods, a considerable amount of WCBs retains certain drawbacks such as long response time, low precision and accuracy. Furthermore, the output signal level does not correspond to a specific analyte concentration value but shows comparative quantification. Here, we utilized a neural network-based architecture to improve the aforementioned features of WCBs and engineered a gold sensing WCB which has a long response time (18 h). Two Long-Short Term-Memory (LSTM)-based networks were integrated to assess both ON/OFF and concentration dependent states of the sensor output, respectively. We demonstrated that binary (ON/OFF) network was able to distinguish between ON/OFF states as early as 30 min with 78% accuracy and over 98% in 3 h. Furthermore, when analyzed in analog manner, we demonstrated that network can classify the raw fluorescence data into pre-defined analyte concentration groups with high precision (82%) in 3 h. This approach can be applied to a wide range of WCBs and improve rapidness, simplicity and accuracy which are the main challenges in synthetic biology enabled biosensing.

synthetic biology↗