Biology subjects

Gul, A.

Publications and source records attributed to Gul, A..

10 recordsLinked to original sources

bioRxiv2026

A platform for high-throughput and ultrasensitive immunopeptidomics

Mass spectrometry (MS)-based immunopeptidomics is a powerful approach for untargeted discovery of peptides presented on major histocompatibility complex (MHC) molecules, which can guide the selection of vaccine antigens and immunotherapy targets. First-generation immunopeptidomics workflows require processing of hundreds of millions of cells using lengthy, manual procedures. More recent approaches focus on increasing either sensitivity or throughput, but rarely combine both aspects. Here, we describe a semi-automated immunopeptidomics platform that combines high sensitivity with high throughput by implementing highly optimized conditions for immunoprecipitation, elution and purification of MHC class I and II peptides on a 96-well positive-pressure device. Upon analysis of 25% of the eluate from 16 million cells, our workflow identified over 13,500 MHC I and 6,000 MHC II peptides on a timsTOF SCP mass spectrometer, operating in DDA-PASEF mode. Exploring the sensitivity limits of our platform, we identified over 1,000 MHC I peptides from as few as 20,000 JY cells. Validating the platforms performance for quantitative biological discovery, we report the identification of known and novel bacterial immunopeptides from U937 macrophages infected with Listeria monocytogenes or Bacillus Calmette-Guerin (BCG). Together, our optimized immunopeptidomics platform enables robust immunopeptide detection from lower-input samples in a high-throughput fashion, enabling its use for biological applications where sample amounts are limiting.

immunology↗

bioRxiv2025

Mapping the Peptide Interaction Fingerprint of the Behcet's disease associated HLA-B*51

The strongest genetic risk factor for Behcets disease, a relapsing inflammatory disorder marked by recurrent mucocutaneous ulcers and uveitis, is an allele of the class I major histocompatibility complex (MHC-I) molecule, which presents intracellular peptides to CD8+ T cells. The molecular mechanisms linking the peptide preferences of this allele (HLA-B*51:01) to dysregulated immunity remain unclear, limiting efforts to design peptide-based modulators of antigen presentation. Here, we define HLA-B*51:01s peptide selection rules by mapping the "interaction fingerprint" of 36 self-peptides using long-duration all-atom MD simulations. These uncovered a conserved hydrophobic-polar blueprint that is tuned by peptide length. High-speed atomic force microscopy rate in silico pulling experiments suggest a three-tier hierarchy of mechanical resilience: 9-mers resist the highest forces, 8-mers exhibit intermediate resistance, and 10/11-mers rupture most easily. Our comprehensive analysis provides an atomistic framework for understanding the molecular mechanisms underlying HLA-B*51:01 pathobiology and offers quantitative parameters to guide the design of therapeutic peptides or small molecules to modulate antigen presentation in Behcets disease. STATEMENT OF SIGNIFICANCEBehcets disease is strongly linked to HLA-B*51:01, a molecule that displays protein fragments to killer T cells, yet how this allele selects its peptides is poorly understood. Here, we combine all-atom equilibrium molecular dynamics simulations with steered MD pulling simulations that mimic high-speed atomic force microscopy experiments to map how 36 self-peptides of different lengths engage the HLA-B*51:01 groove. We uncover a conserved hydrophobic-polar interaction blueprint and show that 9-mers form the mechanically most resilient complexes, whereas shorter or longer peptides detach more easily under force. This length-tuned interaction "fingerprint" provides an atomistic framework for understanding HLA-B*51:01-driven immune dysregulation and guides the rational design of peptide-based or small-molecule modulators for Behcets disease.

biophysics↗

bioRxiv2025

3D Biomimetic Liver Cancer Model: Diethylnitrosamine-Induced Proteomic Dysregulations in Stromal-Epithelial Milieu

Hydrogel-based three-dimensional (3D) co-culture systems are emerging as biomimetic platforms that more accurately recapitulate tissue architecture and microenvironmental interactions compared to conventional two-dimensional (2D) cultures. This study introduces an engineered 3D liver-like model to investigate compartment-specific responses to the potent hepatocarcinogen Diethylnitrosamine (DEN), with a focus on early events in carcinogenesis and tumor-stroma interactions. AML12 and 3T3 cell lines were treated with DEN or vehicle either in 2D culture or in 3D hydrogels in four experimental groups: (1) DEN-treated AML12 with vehicle-treated 3T3, (2) DEN-treated 3T3 with vehicle-treated AML12, (3) both cell types DEN-treated, and (4) both vehicle-treated. The cultured recombinants were subjected to proteomic profiling via mass spectrometry, followed by bioinformatics analysis and the results were validated through immunocytochemical staining (ICC). Gene ontology analysis revealed that cytoskeletal, RNA metabolism, and scaffold/adaptor proteins were among the most significantly enriched in 3D versus 2D models. Structural proteins emerged exclusively in mixed 3D co-cultures, reinforcing the organotypic nature of the system. Enriched pathways in 3D included intermediate filament organization, actin dynamics, and focal adhesion--pathways closely associated with liver carcinogenesis. Protein-protein interaction analysis demonstrated maximal network complexity in 3D cultures where both compartments were DEN-exposed. Survival analysis further identified poor-prognosis biomarkers (KRT20, KRT15, KRT14) uniquely enriched in this condition. ICC staining supported the proteomic findings. This organoid-like 3D co-culture model provides a physiologically relevant platform for investigating early-stage liver carcinogenesis and highlights the critical role of stromal-epithelial interactions. Its ability to replicate organ-level complexity and generate clinically relevant proteomic signatures supports its utility in translational cancer research and future drug discovery applications.

cancer biology↗

bioRxiv2025

Differential Proteomic Analysis of DEN-Induced Hepatocellular Carcinoma in Male and Female Balb/c Mice Reveals Novel Gender Specific Markers

BackgroundHepatocellular carcinoma (HCC) is one of the leading causes of hepatic malignancy with a higher prevalence in males compared to females, however, the distinct underlying mechanisms contributing to this disparity remain poorly understood. MethodsIn this study, we aimed to investigate comparative proteome profiling of a diethylnitrosamine (DEN) induced HCC model in male and female Balb/c mice. We extracted proteins from liver tissue of DEN treated male and female mice and their corresponding controls and subjected them to mass spectrometry and subsequent bioinformatics analyses. ResultsWe identified 170 and 233 differentially expressed proteins (DEPs) in female and male mice, respectively. We identified chemical carcinogenesis and cortical cytoskeleton as the shared pathways between the two groups. In addition, we identified distinct signaling pathways in DEN-treated male and female mice. Female mice showed enrichment in oxidative phosphorylation, fatty acid biosynthesis, metabolism and degradation and cytochrome P450 clusters. In contrast, in male mice, these pathways were enriched in cholesterol metabolism, coagulation and mRNA processing. Further, we identified top ten genes ranked by highest maximal clique centrality, by protein-protein interaction analysis of differentially expressed proteins (DEPs) in both sexes. Of these hub genes, female mice showed upregulation of NDUFA8 and ATP5H and were associated with poor patient survival. On the other hand, In DEN-treated male mice upregulation of FGG, FGA, HPX and SERPINC1 were associated with poor survival. ConclusionIn conclusion, our research provides gender-specific proteomic signatures in DEN-induced HCC. The identification of proteins associated cholesterol metabolism and coagulation in males, and mitochondrial complex I proteins in females as prognostic markers suggests novel therapeutic targets that may inform gender-tailored treatment strategies for HCC. Simple SummaryHepatocellular carcinoma (HCC) is a common and deadly liver cancer that affects men more than women. To understand the biological reasons behind this difference, we developed a liver cancer model in male and female mice using a chemical called diethylnitrosamine (DEN). We then studied the proteins involved in tumor development using advanced techniques like mass spectrometry and bioinformatics. We found that different sets of proteins and biological pathways were active in males and females. In males, ribosomal and RNA-binding proteins were linked to worse survival, while in females, mitochondrial proteins were more important. These findings suggest that men and women may need different strategies for diagnosing and treating HCC, and they offer new gender-specific targets for future therapies.

cancer biology↗

bioRxiv2024

Maximizing immunopeptidomics-based bacterial epitope discovery by multiple search engines and rescoring

Mass spectrometry-based discovery of bacterial immunopeptides presented by infected cells allows untargeted discovery of bacterial antigens that can serve as vaccine candidates. However, reliable identification of bacterial epitopes is challenged by their extreme low abundance. Here, we describe an optimized bioinformatical framework to enhance the confident identification of bacterial immunopeptides. Immunopeptidomics data of cell cultures infected with Listeria monocytogenes were searched by four different search engines, PEAKS, Comet, Sage and MSFragger, followed by data-driven rescoring with MS2Rescore. Compared to individual search engine results, this integrated workflow boosted immunopeptide identification by an average of 27% and led to the high-confidence detection of 18 additional bacterial peptides (+27%) matching 15 different Listeria proteins (+36%). Despite the strong agreement between the search engines, a small number of spectra (< 1%) had ambiguous matches to multiple peptides and were excluded to ensure high-confident identifications. Finally, we demonstrate our workflow with sensitive timsTOF SCP data acquisition and find that rescoring, now with inclusion of ion mobility features, identifies 76% more peptides compared to Q Exactive HF acquisition. Together, our results demonstrate how integration of multiple search engine results along with data-driven rescoring maximizes immunopeptide identification, boosting the detection of high-confidence bacterial epitopes for vaccine development.

molecular biology↗

bioRxiv2024

Role of Mutual Information Profile Shifts in Assessing the Pathogenicity of Mutations on Protein Functions: The case of Pyrin Mutations

This paper presents a novel method to assess the pathogenicity of Pyrin protein mutations by using mutual information (MI) as a measure to quantify the correlation between residue motions or fluctuations and associated changes affecting the phenotype. The concept of MI profile shift is presented to quantify changes in MI upon mutation, revealing insights into residue-residue interactions at critical positions. We apply this method to the Pyrin protein variants, which are associated with an autosomal recessively inherited disease called familial Mediterranean fever (FMF) since the available tools do not help predict the pathogenicity of the most penetrant variants. We demonstrate the utility of MI profile shifts in assessing the effects of mutations on protein stability, function, and disease phenotype. The importance of MI shifts, for the pyrin example the negative shifts, as indicators of severe functional effects is emphasized, along with exploring potential compensatory mechanisms indicated by positive MI shifts, which are otherwise random and inconsequential. The paper also discusses challenges in relating MI profile changes to disease severity and advocates for comprehensive analysis considering genetic, environmental, and stochastic factors. Overall, this study provides insights into the molecular mechanisms underlying the pathogenesis of FMF and offers a framework for identifying potential therapeutic targets based on MI profile changes induced by mutations.

bioinformatics↗

bioRxiv2024

PhysMAP - interpretable in vivo neuronal cell type identification using multi-modal analysis of electrophysiological data

Cells of different types perform diverse computations and coordinate their activity during sensation, perception, and action. While electrophysiological approaches can measure the activity of many neurons simultaneously, assigning cell type labels to these neurons is an open problem. Here, we develop PhysMAP, a framework that weighs multiple electrophysiological modalities simultaneously in an unsupervised manner and obtain an interpretable representation that separates neurons by cell type. PhysMAP is superior to any single electrophysiological modality in identifying neuronal cell types such as excitatory pyramidal, PV+ interneurons, and SOM+ interneurons with high confidence in both juxtacellular and extracellular recordings and from multiple areas of the mouse brain. PhysMAP built on ground truth data can be used for classifying cell types in new and existing electrophysiological datasets, and thus facilitate simultaneous assessment of the coordinated dynamics of multiple neuronal cell types during behavior.

neuroscience↗

bioRxiv2022

Immunopeptidomics-based design of highly effective mRNA vaccine formulations against Listeria monocytogenes

Listeria monocytogenes is a foodborne intracellular bacterial pathogen leading to human listeriosis. Despite a high mortality rate and increasing antibiotic resistance no clinically approved vaccine against Listeria is available. Attenuated Listeria strains offer protection and are tested as antitumor vaccine vectors, but would benefit from a better knowledge on immunodominant vector antigens. To identify novel antigens, we screened for Listeria epitopes presented on the surface of infected human cell lines by mass spectrometry-based immunopeptidomics. In between more than 15,000 human self-peptides, we detected 68 Listeria epitopes from 42 different bacterial proteins, including several known antigens. Peptide epitopes presented on different cell lines were often derived from the same bacterial surface proteins, classifying these antigens as potential vaccine candidates. Encoding these highly presented antigens in lipid nanoparticle mRNA vaccine formulations resulted in specific CD8+ T-cell responses and high levels of protection in vaccination challenge experiments in mice. Our results pave the way for the development of a clinical mRNA vaccine against Listeria and aid to improve attenuated Listeria vaccines and vectors, demonstrating the power of immunopeptidomics for next-generation bacterial vaccine development.

immunology↗

bioRxiv2021

The master energy homeostasis regulator PGC-1alpha couples transcriptional co-activation and mRNA nuclear export

PGC-1 plays a central role in maintaining the mitochondrial and energy metabolism homeostasis, linking external stimuli to the transcriptional co-activation of genes involved in adaptive and age-related pathways. The carboxyl-terminus encodes a serine/arginine-rich (RS) region and a putative RNA recognition motif, however potential RNA-processing role(s) have remained elusive for the past 20 years. Here, we show that the RS domain of human PGC-1 directly interacts with RNA and the nuclear RNA export factor NXF1. Inducible depletion of endogenous PGC-1 and expression of RNAi-resistant RS-deleted PGC-1 further demonstrate that the RNA-binding activity is required for nuclear export of co-activated transcripts and mitochondrial homeostasis. Moreover, a quantitative proteomics approach confirmed PGC-1-dependent RNA transport and mitochondrial-related functions, identifying also novel mRNA nuclear export targets in age-related telomere maintenance. Discovering a novel function for a major cellular homeostasis regulator provides new directions to further elucidate the roles of PGC-1 in gene expression, metabolic disorders, ageing and neurodegenerative diseases.

molecular biology↗

bioRxiv2021

A cell-penetrant peptide blocking C9ORF72-repeat RNA nuclear export suppresses neurodegeneration

Hexanucleotide repeat expansions in C9ORF72 are the most common genetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), a spectrum of incurable debilitating neurodegenerative diseases. Here, we report a novel ALS/FTD drug concept with in vivo and in vitro therapeutic activity in preclinical models of C9ORF72-ALS/FTD. Our data demonstrate that supplementation or oral administration of a cell-penetrant peptide, which competes with the SRSF1:NXF1 interaction, confers neuroprotection by inhibiting the nuclear export of pathological C9ORF72-repeat transcripts in various models of disease including primary neurons, patient-derived motor neurons and Drosophila. Our drug-like rationale for disrupting the nuclear export of microsatellite repeat transcripts in neurological disorders provides a promising alternative to conventional small molecule inhibitors often limited by poor blood-brain barrier penetrance.

molecular biology↗