Biology subjects

Farhat, A.

Publications and source records attributed to Farhat, A..

10 recordsLinked to original sources

bioRxiv2026

Gut-Associated Metabolites (GAMs) revitalize dysfunctional CD8⁺ T lymphocytes in Osteosarcoma

Osteosarcoma (OS) is one of the top ranking and deadliest primary malignant bone tumor of youngsters and adolescents. OS has poor prognostic features due to its immunosuppressive "cold" tumor microenvironment, obstructing the anti-tumor effector functions of immune cells (including cytotoxic CD8 T lymphocytes). Recent developments have focused on the role of Gut Microbiota in modulating effector immune responses in various cancers. However, the immunomodulatory role of gut microbiota and its derived gut-associated metabolites (GAMs) in OS still remains unclear. Here we report that peripheral CD8 T lymphocytes in osteosarcoma patients are less frequent in circulation, hypo-producers of effector cytokines (IFN-{gamma} and TNF-), and have compromised metabolic fitness. We characterized and investigated the effect of a panel of microbiota-derived GAMs on CD8 T lymphocytes, confirming their immunomodulatory role with respect to CD8 T lymphocytes activation, cellular metabolism and effector functions. Indole-3-lactic acid (ILA; product of tryptophan metabolism), was observed to be the strongest immunostimulant among all the GAMs studied. ILA enhanced the anti-tumor effector functions of CD8 T lymphocytes through increased glucose uptake, a higher mitochondrial bio-mass and increased production of IFN-{gamma} and TNF-. Moreover, ILA-primed cytotoxic T lymphocytes exhibited considerably higher cytotoxicity and increased apoptosis of osteosarcoma cells (U2OS). Altogether, our data demonstrates that ILA acts as a microbial-derived immune modulator to metabolically reprogram and restore dysfunctional CD8 T lymphocytes against osteosarcoma. This study for the first time demonstrates the therapeutic potential of exploiting the nexus between "Gut-Immune-Bone Tumor" ternary as a safe and cost-effective combinatorial immunotherapy against osteosarcoma. Graphical AbstractIndole-3-Lactic Acid (ILA) Reinvigorates CD8+ T-Cell Immunity in Osteosarcoma Circulating CD8+ T cells from osteosarcoma patients exhibit impaired metabolic fitness, reduced effector cytokine production, and diminished tumoricidal activity. Screening of gut-associated metabolites identified the microbial tryptophan metabolite indole-3-lactic acid (ILA) as the most potent immunomodulator. ILA restores glucose uptake and mitochondrial biomass, enhances IFN-{gamma} and TNF- production, promotes polyfunctional CD8+ T-cell responses, and significantly improves CTL-mediated killing of osteosarcoma cells, highlighting its potential as a microbiota-derived immunometabolic therapeutic for osteosarcoma. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/741694v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@19809aforg.highwire.dtl.DTLVardef@a3eb09org.highwire.dtl.DTLVardef@19bada3org.highwire.dtl.DTLVardef@1a4c4da_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2026

G-SPRI: A Structure-Centric Graph Model for Comprehensive Prediction of Cancer Driver Events from Missense Mutations

In silico approaches for predicting the functional impact of missense mutations are critical for interpreting personal genomes and identifying disease-related biomarkers. Existing methods largely rely on sequence-based information or intuitive structural features, but often overlook the complex biophysical patterns encoded in protein 3D structures. Here, we present G-SPRI, a multilevel framework built on a novel alpha-shape protein graph that accurately captures residue connectivity from atomic-resolution geometry and enables precise message passing around mutation sites. Using this graph representation, G-SPRI integrates wild-type structural properties and mutation-specific perturbation signals derived from the Protein Data Bank (PDB) universe to support graph-based learning for distinguishing pathogenic from benign missense variants. G-SPRI performs strongly across multiple key tasks. On the binary prediction benchmark, G-SPRI delivers improved pathogenicity prediction for individual mutations. By integrating mutation recurrence across the pan-cancer cohort, G-SPRI recovers more known cancer driver genes than state-of-the-art methods from more than 2.3 million mutations. Furthermore, by jointly quantifying site-specific pathogenicity and co-clustering influence within higher-order structural organization units, G-SPRI provides comprehensive evidence for pinpointing likely driver mutations and structurally susceptible regions within disease genes.

bioinformatics↗

bioRxiv2026

Quantum kernel support vector machines for trabecular bone classification: comparing feature reduction strategies on synthetic micro-CT data

Quantum kernel methods offer a potential advantage for classification tasks in high-dimensional feature spaces, yet their practical benefit critically depends on how input features are prepared. We compare five dimensionality reduction strategies--principal component analysis (PCA), Gaussian random projection (RP Gaussian), sparse random projection (RP Sparse), partial least squares (PLS), and uniform manifold approximation and projection (UMAP) -- as pre-processing steps for quantum kernel support vector machines (SVMs) applied to trabecular bone classification from synthetic micro-computed tomography (micro-CT) data. Using a custom procedural generator based on Gaussian random field zero-crossings, we produced 500 synthetic trabecular bone volumes with controlled morphometric properties such as bone volume fraction (BV/TV), trabecular thickness (Tb.Th), number (Tb.N) and spacing (Tb.Sp). Texture features extracted from grayscale slices are reduced to 8-dimensional quantum circuit inputs via each method, then classified using both classical radial basis function (RBF)-SVMs and quantum kernel SVMs with ZZ feature maps on a statevector simulator, both evaluated with 5 x 5 repeated stratified cross-validation (25 folds). Our results show that UMAP is the only reduction method where the quantum kernel remains competitive with the classical baseline. Under repeated cross-validation, UMAP showed a +0.032 accuracy gap favouring the quantum kernel (Dietterich 5 x 2 CV p = 0.177); however, validation on 10 fully independent datasets--each with independently generated samples, separate reduction fits, and separate kernel matrices -- reversed the sign to -0.030 (paired t-test p = 0.123; Wilcoxon p = 0.193; quantum wins 3/10 datasets), indicating that the apparent advantage was likely inflated by fold dependence. Nevertheless, UMAPs gap remains small and non-significant in both analyses, whereas all linear methods (PCA, RP Gaussian, PLS) show substantial quantum deficits of -0.090 to -0.116 across BV/TV classification, with PCA and PLS remaining significant under corrected tests (5 x 2 CV p = 0.004 and p = 0.007 respectively). We additionally evaluate quantum kernel ridge regression for continuous morphometric prediction, finding that ZZ quantum kernels fail uniformly at regression (negative R2 for all methods except PLS at 4 qubits), suggesting that the ZZ kernel captures decision boundaries but not smooth metric structure. These findings provide practical guidance for feature engineering in near-term quantum machine learning pipelines and demonstrate that the choice of dimensionality reduction can determine whether quantum kernels remain competitive with classical baselines.

biophysics↗

bioRxiv2026

Scaling Multiplex qPCR Primer Design to 1000-plex using the Degenerate Incomplete Multiplex Primer List Extension (DIMPLE) Algorithm

Massively multiplexed qPCR is primarily constrained by increasing primer dimer formation as the number of distinct primers in a single reaction increases. Previous multiplex primer design algorithms either fail to sufficiently suppress primer dimers at 100+ plex, or take exceedingly high amounts of computational resources to complete. Here, we present DIMPLE, a linear-runtime primer design algorithm that effectively generates 10,000+ primers to amplify thousands of potential amplicons in a single qPCR reaction. As one clinical demonstration of this algorithm, we designed an assay to detect 2,302 distinct KMT2A gene fusion subtypes using 204 primers in a single tube. In contrast to FISH and convention NGS approaches with 2% variant allele frequency (VAF) limit of detection, our DIMPLE qPCR assay was able to analytically detect gene fusions down to 0.05% VAF. We also constructed proof-of-concept multiplex qPCR panels for additional oncology gene fusions, multiplex pathogen detection, and DNA methylation markers. The scalability and low computational cost DIMPLE are complementary to new instrument platforms for massively multiplex qPCR readout for enabling rapid, point-of-care nucleic acid testing.

bioengineering↗

bioRxiv2023

H3K9 methylation enhances HP1-associated epigenetic silencing complex assembly and suppresses off-chromatin binding

Visualizing and measuring molecular-scale interactions in living cells represents a major challenge, but recent advances in microscopy are bringing us closer to achieving this goal. Single-molecule super-resolution microscopy enables high-resolution and sensitive imaging of the positions and movement of molecules in living cells. HP1 proteins are important regulators of gene expression because they selectively bind and recognize H3K9 methylated (H3K9me) histones to form heterochromatin-associated protein complexes that silence gene expression. Here, we extended live-cell single-molecule tracking studies in fission yeast to determine how HP1 proteins interact with their binding partners in the nucleus. We measured how genetic perturbations that affect H3K9me alter the diffusive properties of HP1 proteins and each of their binding partners based on which we inferred their most likely interaction sites. Our results indicate that H3K9me promotes specific complex formation between HP1 proteins and their interactors in a spatially restricted manner, while attenuating their ability to form off-chromatin complexes. As opposed to being an inert platform or scaffold to direct HP1 binding, our studies propose a novel function for H3K9me as an active participant in enhancing HP1-associated complex formation in living cells.

biophysics↗

bioRxiv2022

A neutrophil-B-cell axis governs disease tolerance during sepsis via Cxcr4

Sepsis is a life-threatening condition characterized by uncontrolled systemic inflammation and coagulation, leading to multi-organ failure. Therapeutic options to prevent sepsis-associated immunopathology remain scarce. Here, we established a model of long-lasting disease tolerance during severe sepsis, manifested by diminished immunothrombosis and organ damage in spite of a high pathogen burden. We found that, both neutrophils and B cells emerged as key regulators of tissue integrity. Enduring changes in the transcriptional profile of neutrophils, included upregulated Cxcr4 expression in protected, tolerant hosts. Neutrophil Cxcr4 upregulation required the presence of B cells, suggesting that B cells promoted tissue tolerance by suppressing tissue damaging properties of neutrophils. Finally, therapeutic administration of a Cxcr4 agonist successfully promoted tissue tolerance and prevented liver damage during sepsis. Our findings highlight the importance of a critical B-cell/neutrophil interaction during sepsis and establish neutrophil Cxcr4 activation as a potential means to promote disease tolerance during sepsis. SummaryWe show that a B cell/neutrophil interaction in the bone marrow facilitates tissue tolerance during severe sepsis. By affecting neutrophil Cxcr4 expression, B cells can impact neutrophil effector functions. Finally, therapeutic activation of Cxcr4 successfully promoted tissue tolerance and prevented liver damage during sepsis.

immunology↗

bioRxiv2022

A subset of gut leukocytes have telomerase-dependent 'hyper-long' telomeres and require telomerase for function in zebrafish

Telomerase, the enzyme capable of elongating telomeres, is usually restricted in human somatic cells, which contributes to progressive telomere shortening with cell-division and ageing. Using the zebrafish model, we show that subsets gut immune cells have telomerase-dependent "hyper-long" telomeres, which we identified as being predominantly macrophages and dendritics (mpeg1.1+ and cd45+mhcII+). Notably, mpeg+ macrophages have much longer telomeres in the gut than in their haematopoietic tissue of origin, suggesting that there is a gut-specific modulation of telomerase in these cells. Moreover, we show that a subset of gut mpeg+ cells express telomerase (tert) in young WT zebrafish, but that the relative proportion of these cells decreases with ageing. Importantly, this is accompanied by telomere shortening and DNA damage responses with ageing and a telomerase-dependent decrease in expression of autophagy and immune activation markers. Finally, these telomerase-dependent molecular alterations are accompanied by impaired phagocytosis of E.coli and increased gut permeability in vivo. Together, our data show that limiting levels of telomerase lead to changes in gut immunity and gut permeability, which, together, are likely contributors to local and systemic tissue degeneration and increased susceptibility to infection with ageing. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=143 SRC="FIGDIR/small/478480v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@141a6caorg.highwire.dtl.DTLVardef@12d24baorg.highwire.dtl.DTLVardef@c64267org.highwire.dtl.DTLVardef@319449_HPS_FORMAT_FIGEXP M_FIG C_FIG Our data show that limiting levels of telomerase contribute to alterations in gut immunity, namely increased apoptosis, decreased autophagy and immune activation of mpeg+ macrophages in the gut. This is accompanied by a decreased ability to clear pathogens and increased gut permeability. Together, these are likely contributors to local and systemic tissue degeneration and susceptibility to infection with ageing.

cell biology↗

bioRxiv2021

Mapping biochemical states associated with HP1 target recognition at sites of heterochromatin formation in living cells

HP1 proteins bind with low affinity but high specificity to histone H3 lysine 9 methylation (H3K9me), forming transcriptionally inactive genomic compartments referred to as heterochromatin. How HP1 proteins traverse a complex and crowded chromatin landscape on the millisecond timescale and yet recognize H3K9me with high specificity remains paradoxical. Here, we visualize the single-molecule dynamics of an HP1 homolog, the fission yeast Swi6, in its native chromatin environment. By analyzing the motions of individual Swi6 molecules, we identify mobility states that map to discrete biochemical intermediates. Using mutants that perturb Swi6 H3K9me recognition, oligomerization, or nucleic acid binding, we parse the mechanism by which each biochemical property affects protein dynamics. We find that rather than enhancing chromatin binding, nucleic acid interactions, compete with and titrates Swi6 away from heterochromatin. However, as few as four tandem Swi6 chromodomains are necessary and sufficient to restore H3K9me-dependent localization. Our studies propose propose that HP1 oligomerization stabilizes higher-order protein configurations of a defined stoichiometry that facilitates high-specificity H3K9me recognition and outcompetes the inhibitory effects of nucleic acid-binding.

biophysics↗

bioRxiv2021

Topological Sholl Descriptors For Neuronal Clustering and Classification

MotivationGiven that neuronal morphology can widely vary among cell classes, brain regions, and animal species, accurate quantitative descriptions allowing classification of large sets of neurons is essential for their structural and functional characterization. However, robust and unbiased computational methods currently used to characterize groups of neurons are scarce. ResultsIn this work, we introduce a novel and powerful technique to study neuronal morphologies. We develop mathematical descriptors that quantitatively characterize structural differences among neuronal cell types and thus allow for their accurate classification. Each Sholl descriptor that is assigned to a neuron is a function of a distance from the soma with values in real numbers or more general metric spaces. To illustrate the use of Sholl descriptors, six datasets were retrieved from the large public repository http://neuromorpho.org/ comprising neuronal reconstructions from different species and brain regions. Sholl descriptors were subsequently computed, and standard clustering methods enhanced with detection and metric learning algorithms were then used to objectively cluster and classify each dataset. Importantly, our descriptors outperformed conventional techniques and thus provide a practical and effective approach to the classification of diverse neuronal cell types, with the potential for discovery of subclasses of neurons.

neuroscience↗

bioRxiv2017

Systems biology analysis of mitogen activated protein kinase inhibitor resistance in malignant melanoma

Kinase inhibition in the mitogen activated protein kinase (MAPK) pathway is a standard therapy for cancer patients with activating BRAF mutations. However, the anti-tumorigenic effect and clinical benefit are only transient, and tumors are prone to treatment resistance and relapse. To elucidate mechanistic insights into drug resistance, we have established an in vitro cellular model of MAPK inhibitor resistance in malignant melanoma. The cellular model evolved in response to clinical dosage of BRAF inhibitor, vemurafenib, PLX4032. We profiled transcriptomic changes using RNA-Seq and RT-qPCR arrays. Pathways of melanogenesis, MAPK signaling, cell cycle, and metabolism were significantly enriched among the set of differentially expressed genes of vemurafenib-resistant cells vs control. The transcriptomic changes were validated in two distinct melanoma models, SK-MEL-28 and A375. Both cell lines have activating BRAF mutations and display metastatic potential. Downregulation of tumor suppressors and negative MAPK regulators, dual specific phosphatases, reengages mitogenic signaling. Upregulation of growth factors or cytokine receptors triggers signaling pathways circumventing BRAF blockage. Changes in amino acid and one-carbon metabolism support cellular proliferation despite MAPK inhibitor treatment. In addition, an upregulation of pigmentation in inhibitor resistant melanoma cells was observed. Cellular pathways utilized during inhibitor resistance promoted melanogenesis, a pathway which partially overlaps with MAPK signaling. Upstream regulator analysis suggested gene expression changes of forkhead box and hypoxia inducible factor family transcription factors. The established cellular models offer mechanistic insight into cellular changes and therapeutic targets under inhibitor resistance in malignant melanoma. At a systems biology level, the MAPK pathway undergoes major rewiring while acquiring inhibitor resistance. The outcome of this transcriptional plasticity is selection for a set of transcriptional master regulators, which circumvent upstream targeted kinases and provide alternative routes of mitogenic activation. A fine-woven network of redundant signals maintains similar effector genes allowing for tumor cell survival and malignant progression in therapy resistant cancer.

systems biology↗