Biology subjects

Fiser, A.

Publications and source records attributed to Fiser, A..

12 recordsLinked to original sources

bioRxiv2026

XL-MS-Guided Structure Prediction of Disordered Encephalitozoon hellem Proteins

Microsporidia such as Encephalitozoon hellem are obligate intracellular human parasites that remain genetically intractable, limiting functional characterization of their proteomes. Structural studies based on homology-based modeling and the use of deep learning algorithms of microsporidian proteins also remain limited because most have little to no sequence similarity to proteins with solved structures. To address these limitations, we developed an approach that incorporates cross-linking mass spectrometry (XL-MS) data into structure prediction. XL-MS data provides upper bound distance constraints that can be incorporated into protein deep-learning based modeling and subsequent docking. Using this approach, we generated a model for two interacting E. hellem spore wall proteins Spore Wall Protein 1B (Swp1b) and Endospore Protein 1 (EnP1), with no clear homologs outside of microsporidia, and which contain several disordered regions. These proteins are extremely abundant spore wall proteins of microsporidia and previously were not known to interact with one another. The resulting model not only is consistent with the experimental crosslinks used to generate the model but was subsequently confirmed by independently generated XL-MS data. The described AlphaLink-Modeller framework for structure prediction is particularly well suited to proteins with limited homology and/or substantial flexible regions, given they adopt a defined structural state within a biological context, thereby extending integrative modeling approaches to previously inaccessible targets.

microbiology↗

bioRxiv2024

Computational Prediction of Multiple Antigen Epitopes

MotivationIdentifying antigen epitopes is essential in medical applications, such as immunodiagnostic reagent discovery, vaccine design, and drug development. Computational approaches can complement low-throughput, time-consuming, and costly experimental determination of epitopes. Currently available prediction methods, however, have moderate success predicting epitopes, which limits their applicability. Epitope prediction is further complicated by the fact that multiple epitopes may be located on the same antigen and complete experimental data is often unavailable. ResultsHere, we introduce the antigen epitope prediction program ISPIPab that combines information from two feature-based methods and a docking-based method. We demonstrate that ISPIPab outperforms each of its individual classifiers as well as other state-of-the-art methods, including those designed specifically for epitope prediction. By combining the prediction algorithm with hierarchical clustering, we show that we can effectively capture epitopes that align with available experimental data while also revealing additional novel targets for future experimental investigations. Contactraji@yu.edu Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2024

Heterochromatin spreading in cancer cells through HDAC7 mediated histone H3.3 landscape reprogramming.

Class IIa histone deacetylases (HDACs) are a family of enzymes with minimal histone deacetylase activity but can function as multi-protein interaction hubs. Here we demonstrate the expression of HDAC7, a Class IIa HDAC family member, in glioblastoma tumor tissue from 84 patients, patient-derived glioma stem cells (GSCs) from six patients, and pediatric diffuse pontine glioma (DIPG) cells from three patients. HDAC7 binds to Histone H3.3 and interacts with H3.3 and HIRA on chromatin. Targeted downregulation of HDAC7 expression with a subtype-specific siRNA inhibits the interaction of H3.3 with HIRA while increasing the association of H3.3 with DAXX and H3K9me3. This results in H3.3 being deposited on H3K9me3+/DAPI+ heterochromatin nuclear foci. Inhibition of HDAC7 triggers H3K9me3+ heterochromatin spreading, increased H3K9me3 binding in the cancer genome, and significant alterations in gene expression. Using single molecule DNA fiber approach, we show that HDAC7 inhibition results in a significant increase in replication fork speed without affecting fork symmetry. This altered replication fork speed leads to replication stress, evidenced by phosphorylation of RPA2 and impact on global DNA synthesis, resulting in reduced EdU incorporation. Finally, HDAC7 depletion leads to reduced BRCA2 expression and increased sensitivity of cancer cells to DNA damaging agents. Taken together, these studies uncover the involvement of HDAC7 in the euchromatic H3.3 chaperone network and the effect of HDAC7 depletion on chromatin dynamics, inducing epigenetic restriction and DNA damage in cancer cells.

cancer biology↗

bioRxiv2023

Glutamylation of Npm2 and Nap1 acidic disordered regions increases DNA charge mimicry to enhance chaperone efficiency

Histone chaperones-structurally diverse, non-catalytic proteins enriched with acidic intrinsically disordered regions (IDRs)-protect histones from spurious nucleic acid interactions and guide their deposition into and out of nucleosomes. Despite their conservation and ubiquity, the function of the chaperone acidic IDRs remains unclear. Here, we show that the Xenopus laevis Npm2 and Nap1 acidic IDRs are substrates for TTLL4 (Tubulin Tyrosine Ligase Like 4)-catalyzed post-translational glutamate-glutamylation. We demonstrate that, to bind, stabilize, and deposit histones into nucleosomes, chaperone acidic IDRs function as DNA mimetics. Our biochemical, computational, and biophysical studies reveal that glutamylation of these chaperone polyelectrolyte acidic stretches functions to enhance DNA electrostatic mimicry, promoting the binding and stabilization of H2A/H2B heterodimers and facilitating nucleosome assembly. This discovery provides insights into both the previously unclear function of the acidic IDRs and the regulatory role of post-translational modifications in chromatin dynamics.

biochemistry↗

bioRxiv2023

Identification and functional validation of an enhancer variant in the 9p21.3 locus associated with glaucoma risk and elevated expression of p16INK4a

Glaucoma is a leading cause of irreversible blindness, with advanced age being the single most significant risk factor. However, the mechanisms underlying the relationship between aging and glaucoma remain unclear. Genome-wide association studies (GWAS) have successfully identified genetic variants strongly associated with increased glaucoma risk. Understanding how these variants function in pathogenesis is crucial for translating genetic associations into molecular mechanisms and, ultimately, clinical applications. The chromosome 9p21.3 locus is among the most replicated glaucoma risk loci discovered by GWAS. Nonetheless, the absence of protein-coding genes in the locus makes interpreting the disease association challenging, leaving the causal variant and molecular mechanism elusive. In this study, we report the identification of a functional glaucoma risk variant, rs6475604. By employing computational and experimental methods, we demonstrated that rs6475604 resides in a repressive regulatory element. Risk allele of rs6475604 disrupts the binding of YY1, a transcription factor known to repress the expression of a neighboring gene in 9p21.3, p16INK4A, which plays a crucial role in cellular senescence and aging. These findings suggest that the glaucoma disease variant contributes to accelerated senescence, providing a molecular link between glaucoma risk and an essential cellular mechanism for human aging.

genetics↗

bioRxiv2023

Engineering GliaTrap: a biodegradable non-swelling hydrogel with tuned release of CXCL12 to attract migrating glioblastoma cells

Glioblastoma is the most aggressive type of brain cancer with an average overall survival of 15-21 months after first diagnosis. The relapse is mainly caused by migrating glioblastoma cells that diffuse away from the tumor mass into the brain parenchyma and retain cancer stem cell (GSC) properties. Current therapeutic options are ineffective and inevitably result in relapse, indicating a high unmet medical need for innovative therapies in the treatment of invasive glioblastoma. To address this challenge, we propose a new therapeutic modality: GliaTrap, a biodegradable non-swelling, injectable hydrogel with sustained release of a chemoattractant for GSCs that lures and traps the migrating cells back to the tumor resection cavity. We developed a biodegradable and injectable hyaluronan/collagen II-based (HA/Col) hydrogel that does not swell in vivo. The hydrogel is embedded with CXCL12 loaded liposomes and is tuned for sustained release of CXCL12. The safety profile of liposome-embedded HA/Col hydrogel was determined in-vivo after stereotactic implantation in the mouse brain. The efficacy of GliaTrap to attract GSCs was determined ex vivo using a 3D tumor spheroid model and in-vivo using 3D light-sheet microscopy in orthotopic human glioblastoma xenografts. Our findings suggest that GliaTrap could represent a safe and efficacious new therapeutic approach for glioblastoma and potentially serve as a drug delivery platform to locally deliver tumor-killing agents. One Sentence SummaryGliaTrap is a biodegradable non-swelling hydrogel with tuned release of a chemoattractant to attract invading glioma cells and serve as delivery platform for local therapeutics.

cancer biology↗

bioRxiv2023

Assessing the functional impact of protein binding site definition

Many biomedical applications, such as classification of binding specificities or bioengineering, depend on the accurate definition of protein binding interfaces. Depending on the choice of method used, substantially different sets of residues can be classified as belonging to the interface of a protein. A typical approach used to verify these definitions is to mutate residues and measure the impact of these changes on binding. Besides the lack of exhaustive data this approach generates, it also suffers from the fundamental problem that a mutation introduces an unknown amount of alteration into an interface, which potentially alters the binding characteristics of the interface. In this study we explore the impact of alternative binding site definitions on the ability of a protein to recognize its cognate ligand using a pharmacophore approach, which does not affect the interface. The study also provides guidance on the minimum expected accuracy of interface definition that is required to capture the biological function of a protein. AUTHOR SUMMARYThe residue level description or prediction of protein interfaces is a critical input for protein engineering and classification of function. However, different parametrizations of the same methods and especially alternative methods used to define the interface of a protein can return substantially different sets of residues. Typical experimental or computational methods employ mutational studies to verify interface definitions, but all these approaches inherently suffer from the problem that in order to probe the importance of any one position of an interface, an unknown amount of alteration is introduced into the very interface being studied. In this work, we employ a pharmacophore-based approach to computationally explore the consequences of defining alternative binding sites. The pharmacophore generates a hypothesis for the complementary protein binding interface, which then can be used in a search to identify the corresponding ligand from a library of candidates. The accurate ranking of cognate ligands can inform us about the biological accuracy of the interface definition. This study also provides a guideline about the minimum required accuracy of protein interface definitions that still provides a statistically significant recognition of cognate ligands above random expectation, which in turn sets a minimum expectation for interface prediction methods.

bioinformatics↗

bioRxiv2022

EGR2 promoter antisense RNA coordinates chromatin remodeling and spatial genome organization in Schwann cells.

The EGR2 promoter antisense RNA (AS-RNA) recruits chromatin remodeling complexes to inhibit EGR2 transcription following peripheral nerve injury. Here we show that the EGR2-AS-RNA modulates chromatin accessibility and interacts with two distinct histone modification complexes. It binds to EZH2 and WDR5 and enables targeting of H3K27me3 and H3K4me3 to promoters of EGR2and C-JUN respectively. Expression of the AS-RNA results in reorganization of the global chromatin landscape and quantitative changes in loop formation and in contact frequency at domain boundaries exhibiting enrichment for AP-1 genes. In addition, the EGR2-AS-RNA induces changes in hierarchical TADs and increases transcription factor occupancy on an inter-TAD loop between a super-enhancer regulatory hub and the promoter of mTOR. Our results show that the EGR2-AS-RNA may serve as regulator of chromatin remodeling and spatial genome organization in Schwann cells.

neuroscience↗

bioRxiv2021

Chi3l1 is a modulator of glioma stem cell states and a therapeutic vulnerability for glioblastoma

Chi3l1 (Chitinase 3-like 1) is a secreted protein highly expressed in glioblastoma. Here, we show that exposure of glioma stem cells (GSCs) to Chi3l1 reduces the CD133+/SOX2+ cells and increases the CD44+/Chi3l1+ cells. Chi3l1 binds to CD44 and induces phosphorylation and nuclear translocation of beta-catenin, Akt and STAT3. Single cell RNA-seq and RNA velocity following incubation of GSCs with Chi3l1 show significant changes in GSC state dynamics driving GSCs towards a mesenchymal expression profile and reducing transition probabilities towards terminal cellular states. ATAC-seq reveals that Chi3l1 increases accessibility of promoters containing MAZ transcription factor footprint. Inhibition of MAZ directly regulates genes with highest expression in cellular clusters exhibiting significant cell state transitions. Finally, targeting Chi3l1 in vivo with a blocking antibody, resets the transcriptomic profile of glioblastoma and inhibits tumor growth. Our work implicates Chi3l1 as modulator of GSC cellular states and demonstrates pre-clinical efficacy of anti-Chi3l1 antibody treatment.

cancer biology↗

bioRxiv2020

miRNA-mediated loss of m6A increases nascent translation in glioblastoma

Within the glioblastoma cellular niche, glioma stem cells (GSCs) can give rise to differentiated glioma cells (DGCs) and, when necessary, DGCs can reciprocally give rise to GSCs to maintain the cellular equilibrium necessary for optimal tumor growth. Here, using ribosome profiling, transcriptome and m6A RNA sequencing, we show that GSCs from patients with different subtypes of glioblastoma share a set of transcripts, which exhibit a pattern of m6A loss and increased protein translation during differentiation. The target sequences of a group of miRNAs overlap the canonical RRACH m6A motifs of these transcripts, many of which confer a survival advantage in glioblastoma. Ectopic expression of the RRACH-binding miR-145 induces loss of m6A, formation of FTO/AGO1/ILF3/miR-145 complexes on a clinically relevant tumor suppressor gene (CLIP3) and significant increase in its nascent translation. Inhibition of miR-145 maintains RRACH m6A levels of CLIP3 and inhibits its nascent translation. This study highlights a critical role of miRNAs in assembling complexes for m6A demethylation and induction of protein translation during GSC state transition. Author SummaryCellular plasticity and epigenetic adaptation of human glioblastoma stem cells to the tumor microenvironment is a hallmark of this devastating disease. With our present work, we discover the relationship between miRNAs and the RNA methylation machinery in human glioblastoma and show how miRNA-induced loss of m6A results in increase in protein translation of clinically important transcripts during glioblastoma stem cell differentiation. Leveraging the dynamic functions of these miRNAs can be important in the design of optimal therapeutics targeted at cancer cell plasticity.

cancer biology↗

bioRxiv2020

Subventricular zone adult mouse neural stem cells and human glioblastoma stem cells require insulin receptor for self-renewal

The insulin receptor (IR) is an evolutionarily conserved signaling protein that regulates development and cellular metabolism. IR signaling regulates neurogenesis in Drosophila; however, a specific role for the IR in maintaining adult neural stem cells (NSCs) in mammals has not been investigated. We show that conditionally deleting the IR reduces adult NSCs of the subventricular zone by [~]70% accompanied by a corresponding increase in progenitors. IR deletion produced hyposmia due to aberrant olfactory bulb neurogenesis. Interestingly, hippocampal neurogenesis was not perturbed nor were hippocampal dependent behaviors. Highly aggressive proneural and mesenchymal glioblastomas (GBMs) had high IR/insulin-like growth factor (IGF) pathway gene expression, and isolated glioma stem cells had an aberrantly high ratio of IR:IGF1R receptors. Moreover, IR knockdown inhibited proneural and mesenchymal GBM tumorsphere growth. Altogether, these data demonstrate that the IR is essential for a subset of normal NSCs as well as for brain tumor cancer stem cell self-renewal.

neuroscience↗

bioRxiv2019

Expression of c-Fos and Arc in hippocampal region CA1 marks neurons that exhibit learning-related activity changes

Immediate early genes (IEGs) are transcribed in response to neural activity and necessary for many forms of plasticity. However, the dynamics of their expression during learning, as well as their relationship to neural activity, remain unclear. Here we used two-photon imaging in transgenic mice that express a GFP-tagged variant of Arc or c-Fos and a red-shifted calcium indicator to measure learning-related changes in IEG expression levels and neural activity in hippocampal region CA1 as mice learned to perform a two-alternative forced choice task. Neural activity levels correlated positively with IEG expression levels in vivo. In addition, we found that with learning, a subset of neurons in CA1 increased their responses to the reward-predicting cue, and IEG expression levels early in learning were selectively increased in neurons that would exhibit the strongest learning-related changes. Our findings are consistent with an interpretation of IEG expression levels as markers for experience dependent plasticity.

neuroscience↗