Biology subjects

Unger, R.

Publications and source records attributed to Unger, R..

5 recordsLinked to original sources

bioRxiv2022

An affinity for brainstem microglia in pediatric high grade gliomas of brainstem origin

BackgroundHigh-grade gliomas (HGG) in children have a devastating prognosis and occur in a remarkable spatiotemporal pattern. Diffuse midline gliomas (DMG), including diffuse intrinsic pontine gliomas (DIPG), typically occur in mid-childhood, while cortical HGGs are more frequent in older children and adults. The mechanisms behind this pattern are not clear. MethodsWe used mouse organotypic slice cultures and glial cell cultures to test the impact of the microenvironment on human DIPG cells. Comparing the expression between brainstem and cortical microglia identified differentially expressed secreted proteins. The impact of some of these proteins on DIPGs was tested. ResultsDIPGs, pediatric HGGs of brainstem origin, survive and divide more in organotypic slice cultures originating in the brainstem as compared to the cortex. Moreover, brainstem microglia are better able to support tumors of brainstem origin. A comparison between the two microglial populations revealed differentially expressed genes. One such gene, Interleukin-33 (IL33), is highly expressed in the pons of young mice and its DIPG receptor is upregulated in this context. Consistent with this observation, the expression levels of IL33 and its receptor, IL1RL1, are higher in DIPG biopsies compared to low grade cortical gliomas. Furthermore, IL33 can enhance proliferation and clonability of HGGs of brainstem origin, while blocking IL33 in brainstem organotypic slice cultures reduced the proliferation of these tumor cells. ConclusionsCrosstalk between DIPGs and the brainstem microenvironment, in particular microglia, through IL33 and other secreted factors, modulates spatiotemporal patterning of this HGG and could prove to be an important future therapeutic target. Key PointsO_LIDIPGs divide more in the brainstem environment compared to the cortex. C_LIO_LIIL33 expression in brainstem and brainstem microglia is higher than in the cortex of young mice. C_LIO_LIIL33 propagates DIPG tumorigenesis, and its inhibition decreases DIPG proliferation. C_LI Importance of the StudyPediatric gliomas can arise in the supratentorial cerebral cortex with a median diagnosis age of 13 years, while diffuse midline gliomas (DMGs), present a median diagnosis age of 7 years, and appear most frequently in the pons. DMGs have a devastating prognosis and are currently untreatable. We tested the contribution of the brainstem microenvironment to the observed spatiotemporal pattern of pediatric HGGs. Our results support a model in which the brainstem microenvironment, particularly microglia, offers more supportive conditions for DIPG cells. By using the differences in gene expression between brainstem and cortical microglia we were able to identify factors that may contribute to the DIPG preference toward the brainstem. In this study we focused on the factor IL33, and provided evidence to support its contribution to the propagation of DIPGs in this specific anatomical location.

cancer biology↗

bioRxiv2022

DistilProtBert: A distilled protein language model used to distinguish between real proteins and their randomly shuffled counterparts

SummaryRecently, Deep Learning models, initially developed in the field of Natural Language Processing (NLP), were applied successfully to analyze protein sequences. A major drawback of these models is their size in terms of the number of parameters needed to be fitted and the amount of computational resources they require. Recently, "distilled" models using the concept of student and teacher networks have been widely used in NLP. Here, we adapted this concept to the problem of protein sequence analysis, by developing DistilProtBert, a distilled version of the successful ProtBert model. Implementing this approach, we reduced the size of the network and the running time by 50%, and the computational resources needed for pretraining by 98% relative to ProtBert model. Using two published tasks, we showed that the performance of the distilled model approaches that of the full model. We next tested the ability of DistilProtBert to distinguish between real and random protein sequences. The task is highly challenging if the composition is maintained on the level of singlet, doublet and triplet amino acids. Indeed, traditional machine learning algorithms have difficulties with this task. Here, we show that DistilProtBert preforms very well on singlet, doublet, and even triplet-shuffled versions of the human proteome, with AUC of 0.92, 0.91, and 0.87 respectively. Finally, we suggest that by examining the small number of false-positive classifications (i.e., shuffled sequences classified as proteins by DistilProtBert) we may be able to identify de-novo potential natural-like proteins based on random shuffling of amino acid sequences. Availabilityhttps://github.com/yarongef/DistilProtBert Contactyaron.geffen@biu.ac.il

bioinformatics↗

bioRxiv2021

Genome instability drives epistatic adaptation in the human pathogen Leishmania

How genome instability is harnessed for fitness gain despite its potential deleterious effects is largely elusive. An ideal system to address this important open question is provided by the protozoan pathogen Leishmania, which exploits frequent variations in chromosome and gene copy number to regulate expression levels. Using ecological genomics and experimental evolution approaches we provide first evidence that Leishmania adaptation relies on epistatic interactions between functionally associated gene copy number variations in pathways driving fitness gain in a given environment. We further uncover post-transcriptional regulation as a key mechanism that compensates for deleterious gene dosage effects and provides phenotypic robustness to genetically heterogenous parasite populations. Finally, we correlate dynamic variations in snoRNA gene dosage with changes in rRNA 2-O-methylation and pseudouridylation, suggesting translational control is an additional layer of parasite adaptation. Leishmania genome instability is thus harnessed for fitness gain by genome-dependent variations in gene expression, and genome-independent, compensatory mechanisms. This allows for polyclonal adaptation and maintenance of genetic heterogeneity despite strong selective pressure. The epistatic adaptation described here needs to be considered in Leishmania epidemiology and biomarker discovery, and may be relevant to other fast evolving, eukaryotic cells that exploit genome instability for adaptation, such as fungal pathogens or cancer. One Sentence SummaryEpistatic interactions harness genome instability for Leishmania fitness gain.

genomics↗

bioRxiv2021

Post-transcriptional regulation of Leishmania fitness gain

The protozoan parasite Leishmania donovani causes fatal human visceral leishmaniasis in absence of treatment. Genome instability has been recognized as a driver in Leishmania fitness gain in response to environmental change or chemotherapy. How genome instability generates beneficial phenotypes despite potential deleterious gene dosage effects is unknown. Here we address this important open question applying experimental evolution and integrative systems approaches on parasites adapting to in vitro culture. Phenotypic analyses of parasites from early and late stages of culture adaptation revealed an important fitness tradeoff, with selection for accelerated growth in promastigote culture (fitness gain) impairing infectivity (fitness costs). Comparative genomics, transcriptomics and proteomics analyses revealed a complex regulatory network driving parasite fitness, with genome instability causing highly reproducible, gene dosage-dependent changes in protein abundance linked to post-transcriptional regulation. These in turn were associated with a gene dosage-independent reduction in abundance of flagellar transcripts and a coordinated increase in abundance of coding and non-coding RNAs implicated in ribosomal biogenesis and protein translation. We correlated differential expression of small nucleolar RNAs (snoRNAs) with changes in rRNA modification, providing first evidence that Leishmania fitness gain in culture may be controlled by post-transcriptional and epitranscriptomic regulation. Our findings propose a novel model for Leishmania fitness gain in culture, where differential regulation of mRNA stability and the generation of fitness-adapted ribosomes may potentially filter deleterious from beneficial gene dosage effects and provide proteomic robustness to genetically heterogenous, adapting parasite populations. This model challenges the current, genome-centric approach to Leishmania epidemiology and identifies the Leishmania transcriptome and non-coding small RNome as potential novel sources for the discovery of biomarkers that may be associated with parasite phenotypic adaptation in clinical settings.

microbiology↗

bioRxiv2018

Molecular anatomy and plasticity of the long noncoding RNA HOTAIR

Long noncoding RNA molecules (lncRNAs) are estimated to account for the majority of eukaryotic genomic transcripts, and have been associated with multiple diseases in humans. However, our understanding of their structure-function relationships is scarce, with structural evidence coming mostly from indirect biochemical approaches or computational predictions. Here we describe the hypothetical molecular anatomy of the lncRNA HOTAIR (HOx Transcript AntIsense RNA) inferred from direct, high-resolution visualization by atomic force microscopy (AFM) in nucleus-like conditions at 37 degrees. Our observations reveal that HOTAIR has a distinct anatomy with a high degree of plasticity. Fast AFM scanning enabled the quantification of this plasticity, and provided visual evidence of physical interactions with genomic DNA segments. Our report provides the first biologically-plausible hypothetical description of the anatomy and intrinsic properties of HOTAIR, and presents a framework for studying the structural biology of lncRNAs.

biophysics↗