Biology subjects

Shomron, N.

Publications and source records attributed to Shomron, N..

11 recordsLinked to original sources

bioRxiv2026

RNA-sequencing of butyrate-treated human lymphoblastoid cell lines shows dysregulated genes of multiple disease-related pathways

Abstract Butyrate, a 4-carbon fatty acid produced from insoluble starch by the gut microbiome, plays key roles in mitochondrial respiration, activation of cell-surface G-protein-coupled receptors, and protein acetylation by inhibiting histone deacetylases (HDACs). Butyrate (as sodium salt) added to drinking water was shown to improve pathological symptoms in numerous model mouse disorders, including models for cancer metastasis, neuroinflammation, autism spectrum disorders, dementia, insulin resistance, and colorectal cancer. Over 5000 PubMed-listed studies feature butyrate in their title, yet its genome-wide transcriptomic effects have not been reported in human cell lines from multiple healthy donors. Here, we report the genome-wide transcriptomic effects of 1 mM sodium butyrate on human lymphoblastoid cell lines (LCLs) generated from blood samples of eight unrelated healthy donors. Paired bioinformatics analysis comparing the butyrate-treated LCLs to the same untreated cell line identified thousands of differentially expressed gene (DEG) transcripts with padj<0.05, of which over half were upregulated by butyrate. Pathway analysis showed that butyrate exposure of LCLs upregulated extracellular matrix, cell adhesion, junction organization, Wnt signaling, axonogenesis, and neurodevelopment pathways. Downregulated pathways included cell cycle, G2/M checkpoint, E2F/MYC targets, DNA replication and repair, mitotic spindle integrity, mTOR signaling, oxidative phosphorylation, unfolded-protein response, and translation/ribosome-related pathways. Our RNA-seq study, utilizing LCLs from healthy donors and paired bioinformatic analysis, opens venues for assessing butyrate effects on cellular pathways and potential therapeutics for cancer, metabolic, immune, and CNS-related disorders.

genomics↗

bioRxiv2026

Cross-species analysis of GNB1 I80T encephalopathy: conserved developmental, epileptic and neuronal transcriptome signatures

GNB1 encephalopathy (GNB1E) is a rare neurodevelopmental disorder caused by mutations in GNB1 gene encoding the G protein subunit G{beta}1. Mechanisms linking these variants to neurological dysfunction remain unclear. We investigated the prevalent p.Ile80Thr (I80T) variant using combined clinical, cellular, and in vivo approaches. Longitudinal evaluation of a GNB1E patient revealed developmental delay, progressive peripheral spasticity, and epilepsy with Spike-Wave Activation in Sleep. Heterozygous knock-in Gnb1I80T/+ mice exhibited disease-relevant phenotypes, including impaired early development, mild adult motor and cognitive deficits and epileptiform cortical spike-and-wave discharges. Transcriptomic analysis identified 323 genes concordantly dysregulated in mouse cortex and cortical human neuronal cultures from patient-derived induced pluripotent cells. This gene set was enriched for ion-channel function, epilepsy-associated genes, and Gs/adenylyl cyclase signaling pathway. Our integrated analysis establishes the first cross-species model for GNB1E, suggests common neurological mechanisms and molecular pathways linked to GNB1E, and provides a framework for mechanistic and therapeutic studies. TeaserConserved human/mouse neurological and transcriptomic signatures in GNB1 encephalopathy.

physiology↗

bioRxiv2026

Comparative analysis of Illumina and Ultima-Genomics sequencing for plasma cell-free small RNA profiling in pancreatic cancer

Plasma-derived cell-free small non-coding RNAs are promising non-invasive biomarkers for cancer detection and monitoring. However, variability in sequencing output limits standardization, and cross-platform performance for plasma small RNA profiling has not been systematically evaluated. Illumina short-read sequencing is the current standard, whereas the newcomer, Ultima-Genomics platform, has been less extensively studied for circulating small RNA in plasma. To directly compare platform performance, we sequenced plasma cell-free RNA from 39 patients with pancreatic cancer and 39 matched controls on both platforms. After filtering, Ultima-Genomics retained more mature microRNA reads, whereas Illumina achieved slightly higher enrichment efficiency and mapping rates. Despite these technical differences, both platforms produced concordant expression profiles, with strong cross-platform correlations for shared microRNAs and clear separation of cases and controls within each dataset. Differential expression analysis identified 14 significant microRNAs on both platforms with concordant directions of change, most of which are supported by pancreatic cancer databases. Pathway enrichment analysis highlighted signaling pathways implicated in pancreatic cancer, supporting the biological relevance of both shared and platform-specific signatures. These findings indicate that both Illumina and Ultima Genomics platforms are suitable for plasma small RNA profiling and capture biologically relevant signals in pancreatic cancer.

genomics↗

bioRxiv2026

Simulation-based Bayesian deep learning enables uncertainty-aware tumor fraction estimation in cell-free DNA

BackgroundEstimating tumor fraction from whole-genome cell-free DNA sequencing is critical for liquid biopsy, but is hampered by weak signals and baseline noise at low tumor fractions. Existing computational methods often require matched controls or large labeled datasets for training and lack uncertainty quantification. To address these gaps, we developed purNPE, a Bayesian deep-learning framework trained without labeled cancer cell-free DNA samples. Specifically, purNPE leverages a two-part generative model: one component simulates diverse tumor copy-number profiles based on evolutionary genealogies, while a second, data-driven component learns and replicates realistic sequencing background patterns from cancer-free cell-free DNA. By training a Neural Posterior Estimator on synthetic tumor profiles augmented with learned noise, purNPE performs amortized inference in milliseconds without needing a reference sample set at inference. ResultsIn a real-world pan-cancer cohort, purNPE achieved comparable performance with existing methods against orthogonal mutant-allele-fraction validation (MAE = 0.066). In silico and semi-synthetic experiments suggested analytical sensitivity around 1% tumor fraction under the evaluated conditions and showed strong classification accuracy in low tumor fractions (AUC = 0.98 for TF[≤] 3% versus controls). ConclusionsThis work provides a framework for using simulation-based inference to derive calibrated, uncertainty-aware TF estimates, offering a potential alternative to traditional data-dependent methods.

bioinformatics↗

bioRxiv2026

Exploring per-base quality scores as a surrogate marker of cell-free DNA fragmentome

Per-base quality scores are widely treated as technical metadata in next-generation sequencing. Here, we show that in rigorously controlled whole-genome sequencing of cell-free DNA, quality profiles may encode fragmentomic signals that enable classification of cancer samples against matched controls. Analyzing four independent batches (23 cancer samples: pancreatic and breast; 22 matched controls) sequenced in a within-lane regime and further normalized per flow-cell tile to reduce technical confounders, we demonstrate through unsupervised analysis that boundary-enriched dynamics captured in these quality scores consistently separate cancer from control samples. A leave-one-batch-out classifier trained on quality-derived scores achieved a pooled area under the curve of 0.81. Furthermore, we show that the quality-derived metric correlates with short-fragment enrichment and tumor-associated 5-end motifs, performing comparably to established, motif-based orthogonal methods. These results provide initial evidence that quality scores could serve as a low-cost, alignment-free biomarker for cfDNA-based cancer detection. Key PointsO_LIPBQS in rigorously controlled cfDNA whole-genome sequencing contain biologically informative fragmentomic signal rather than only technical noise C_LIO_LIBoundary-enriched quality dynamics distinguish cancer samples from matched controls across independent sequencing batches C_LIO_LIA leave-one-batch-out classifier based on PBQS-derived features achieved a pooled AUC of 0.81 across 23 cancer and 22 control samples C_LIO_LIThe PBQS-derived score correlates with short-fragment enrichment and tumor-associated 5' end motifs, supporting its value as a lightweight orthogonal biomarker for cfDNA cancer. C_LI Biographical NoteProf. Noam Shomron heads the Functional Genomics Laboratory at Tel Aviv Universitys Medical School, where his group studies genomics and bioinformatics with a focus on sequencing technologies and translational medicine.

bioinformatics↗

bioRxiv2022

Structure-function conservation between the methyltransferases SETD3 and SETD6

Among the protein lysine methyltransferases family members, it appears that SETD6 is highly similar and closely related to SETD3. The two methyltransferases show high similarity in their structure, which raised the hypothesis that they share cellular functions. Using a proteomic screen, we identified 52 shared interacting-proteins. Gene Ontology (GO) analysis of the shared proteins revealed significant enrichment of proteins involved in transcription. Our RNA-seq data of SETD6 KO and SETD3 KO HeLa cells identified [~]100 up-regulated and down-regulated shared genes. We have also identified a substantial number of genes that changed dramatically in the double KO cells but did not significantly change in the single KO cells. GO analysis of these genes revealed enrichment of apoptotic genes. Accordingly, we show that the double KO cells displayed high apoptotic levels, suggesting that SETD6 and SETD3 inhibit apoptosis. Collectively, our data strongly suggest a functional link between SETD6 and SETD3 in the regulation of apoptosis.

cell biology↗

bioRxiv2021

LY6S, a New Interferon-Inducible Human Member of the Ly6a-Subfamily Expressed by Spleen Cells and Associated with Inflammation and Viral Resistance

Syntenic genomic loci on human chromosome 8 (hChr8) and mouse chromosome 15 (mChr15) code for LY6/Ly6 (lymphocyte antigen 6) family proteins. The 23 murine Ly6 family genes include eight genes that are flanked by the murine Ly6e and Ly6l genes and form an Ly6 subgroup referred to here as the Ly6a subfamily gene cluster. Ly6a, also known as Sca1 (Stem Cell Antigen-1) and TAP (T-cell activating protein), is a member of the Ly6a subfamily gene cluster. No LY6 genes have been annotated within the syntenic LY6E to LY6L human locus. We report here on LY6S, a solitary human LY6 gene that is syntenic with the murine Ly6a subfamily gene cluster, and with which it shares a common ancestry. LY6S codes for the interferon-inducible GPI-linked LY6S-iso1 protein that contains only 9 of the 10 consensus LY6 cysteine residues and is most highly expressed in a non-classical cell population. Its expression leads to distinct shifts in patterns of gene expression, particularly of genes coding for inflammatory and immune response proteins, and LY6S-iso1 expressing cells show increased resistance to viral infection. Our findings reveal the presence of a previously un-annotated human interferon-stimulated gene, LY6S, which has a one to eight ortholog relationship with the genes of the Ly6a subfamily gene cluster, is most highly expressed in spleen cells of a non-classical cell-lineage and whose expression induces viral resistance and is associated with an inflammatory phenotype and with the activation of genes that regulate immune responses. One Sentence SummaryLY6S is a newly discovered human interferon-inducible gene associated with inflammation and with resistance to viral replication.

genomics↗

bioRxiv2021

TWIST1 methylation by SETD6 selectively antagonizes LINC-PINT expression in Glioblastoma multiforme

Glioblastoma multiforme (GBM) is the most common and aggressive malignant brain tumor among adults, which is characterized by high invasion, migration and proliferation abilities. One important process that contributes to the invasiveness of GBM is the epithelial to mesenchymal transition (EMT). EMT is regulated by a set of defined transcription factors which tightly regulate this process, among them is the basic helix-loop-helix family member, TWIST1. Here we show that TWIST1 is methylated on lysine-33 at chromatin by SETD6, a methyltransferase with expression levels correlating with poor survival in GBM patients. RNA-seq analysis in U251 GBM cells suggested that both SETD6 and TWIST1 regulate cell adhesion and migration processes. We further show that TWIST1 methylation attenuates the expression of the long-non-coding RNA, LINC-PINT, thereby suppressing EMT in GBM. Mechanistically, TWIST1 methylation represses the transcription of LINC-PINT by increasing the occupancy of EZH2 and the catalysis of the repressive H3K27me3 mark at the LINC-PINT locus. Under un-methylated conditions, TWIST1 dissociates from the LINC-PINT locus, allowing the expression of LINC-PINT which leads to increased cell adhesion and decreased cell migration. Together, our findings unravel a new mechanistic dimension for selective expression of LINC-PINT mediated by TWIST1 methylation.

molecular biology↗

bioRxiv2021

Genetic and phenotypic heterogeneity in PNPT1, MYO15A, PTPRQ and SLC12A2 variants detected among hearing impaired assortative mating families in Southern India

Exome analysis was used to resolve the etiology of hearing loss (HL) in four South Indian assortative mating families. Six variants, including three novel ones, were identified in four genes: PNPT1 p.Ala46Gly and p.Asn540Ser, MYO15A p.Leu1485Pro and p.Tyr1891*, PTPRQ p.Gln1336*, and SLC12A2 p.Pro988Ser. Compound heterozygous PNPT1 variants were associated with prelingual profound sensorineural hearing loss (SNHL), vestibular dysfunction and unilateral progressive vision loss in one family. In the second family, MYO15A variants in the myosin motor domain, including a novel variant, were found to be associated with prelingual profound SNHL. A novel PTPRQ variant was associated with postlingual progressive sensorineural/mixed HL and vestibular dysfunction in the third family, with mastoid bone hypopneumatization observed in one family member. In the fourth family, the SLC12A2 novel variant was found to segregate with severe-to-profound HL causing DFNA78, across three generations. Our results suggest a high level of allelic, genotypic and phenotypic heterogeneity of HL in these families. This study is the first to report the association of PNPT1, PTPRQ and SLC12A2 variants with HL in the Indian population.

genetics↗

bioRxiv2020

Multi-Modal Single-Molecule Imaging with Continuously Controlled Spectral-resolution (CoCoS) Microscopy

Color is a fundamental contrast mechanism in fluorescence microscopy, providing the basis for numerous imaging and spectroscopy techniques. The ever-growing need to acquire high-throughput, dynamic data from multicolor species is driving the development of optical schemes that optimize the achievable spectral, temporal, and spatial resolution needed in order to follow biological, chemical and physical processes. Here we introduce Continuously Controlled Spectral-resolution (CoCoS) microscopy, an imaging scheme that encodes color into spatial read-out in the image plane, with continuous control over the spectral resolution. The concept enables single-frame acquisition of multiple color channels, allowing simultaneous, single-molecule colocalization for barcoding and Forster resonance energy transfer (FRET) experiments. The simple control over the spectral dispersion allows switching between imaging modalities at a click of a button. We demonstrate the utility of CoCoS for multicolor localization microscopy of microRNA barcodes in clinical samples, single-molecule FRET measurements, and single-molecule spectroscopy. CoCoS may be integrated as a simple add-on to existing microscopes and will find use in applications that aim to record dynamic, multicolor localization events such as in multiplex FRET and tracking of multi-component, interacting complexes.

biophysics↗

bioRxiv2020

Transient cell-in-cell formation underlies tumor resistance to immunotherapy

Despite the remarkable success of immunotherapy in cancer, most patients will develop resistant tumors. While the main conceptual paradigm suggests that relapsed clones emerge through a process of clonal selection and immunoediting, currently little evidence directly demonstrates this process in epithelial cancers. To study this process, we established several mouse models in which tumors drastically regress following immunotherapy, yet resistant tumors relapse within a few weeks of treatment cessation. Whole exome analyses indicated that relapsed tumors share hundreds of neo-antigens with the primary tumors and are comparably killed by reactive T cells. Examination of tumor cells that survive immunotherapies revealed that they structure a transient cell-in-cell formation, which is impenetrable to immune-derived cytotoxic compounds and to chemotherapies. This formation is mediated predominantly by a cell-membrane protein on activated T cells, which subsequently induces epidermal growth factor receptors and STAT3 phosphorylation in tumors cells. In contrast to previous reports on cell-in-cell formations, here both cells remain alive and can disseminate into single tumor cells once T cells are no longer present. Overall, this work highlights a powerful resistance mechanism which enable tumor cells to survive immune pressure and provides a new theoretical framework for combining chemotherapies and immunotherapies.

immunology↗