Biology subjects

Mahmoudi, T.

Publications and source records attributed to Mahmoudi, T..

16 recordsLinked to original sources

bioRxiv2026

Hepatitis B virus protein X promotes hepatocyte plasticity and survival in a differentiated human liver organoid system

Background & AimsHepatitis B virus (HBV) drives hepatocellular carcinoma in part through the activity of its X protein (HBx), yet the mechanisms by which HBx alters hepatocyte function remain incompletely understood. Progress has been limited by the lack of relevant human models that support controlled HBx expression in mature hepatocytes. Here, we use an improved hepatocyte-like organoid (HLO) platform that supports enhanced hepatocyte maturation to investigate HBx function in a differentiated hepatocyte context. MethodsAdult stem cell-derived HLOs were differentiated using an optimized protocol to generate hepatocyte-like cells with enhanced maturation and transcriptional similarity to primary liver tissue. HBx function was interrogated using both cognate promoter-driven expression and doxycycline-inducible systems across multiple donor-derived organoid lines. Transcriptomic, pathway, and single-cell imaging analyses were performed to assess the impact of HBx expression on hepatocytes. ResultsHBx expression consistently suppressed apoptosis-associated transcripts and reduced expression of core hepatocyte identity genes, including CYP3A4. Pathway analysis revealed downregulation of liver-specific functions, including metabolism, detoxification, complement, and coagulation. At the single-cell level, higher HBx expression was associated with reduced caspase 3/7 activation following apoptotic challenge and decreased hepatocyte marker expression. Functionally, HBx expression increased resistance to apoptosis and enhanced the ability of differentiated hepatocyte-like cells to revert to a proliferative, less differentiated state. ConclusionsHBx expression in differentiated human liver organoids reduces apoptosis and impairs hepatocyte identity, consistently across donors and expression systems. These findings support a model in which HBx promotes a survival-permissive less differentiated state that may contribute to early HBV-driven tumorigenesis. This HLO platform provides a relevant system to dissect HBV-host interactions and reveals a mechanism by which HBV may prime the liver for malignant transformation. Impact and implicationsUnderstanding how HBV promotes hepatocellular carcinoma remains a critical challenge, partly due to the lack of physiologically relevant human derived model systems to study HBx function. Using a differentiated adult human liver organoid system, we show that HBx simultaneously suppresses apoptosis and disrupts hepatocyte identity, providing a mechanistic framework for how HBV may prime hepatocytes for malignant transformation. These findings are particularly relevant for researchers studying HBV pathogenesis and liver cancer, as well as for clinicians aiming to better understand early disease progression. While further validation in more complex multicellular systems is needed, this platform can support the identification of HBx-targeted therapeutic strategies and guide the development of improved adult human derived models for virus-host interaction studies.

cell biology↗

bioRxiv2026

Larger inducible reservoir and higher abundance of exhausted CD8+ T cells in people treated after late versus non-late diagnosis of chronic HIV one year after ART initiation

Background Despite effective antiretroviral therapy, HIV-1 remains a global health challenge. Most people living with HIV (PWH) are diagnosed in the chronic stage and around half are diagnosed late globally. Insight into the effect of time of diagnosis and therapy initiation on reservoir dynamics and immune reconstitution within the group with a chronic diagnosis is limited. Methods In this prospective cohort study, PWH diagnosed during the chronic stage (from Fiebig VI) were stratified into late (<350 CD4+ T cells/mm3 or an AIDS-defining illness) or non- late diagnosis subgroups. We analyzed the viral reservoir by IPDA, SQuHIVLa and FISH-Flow, and the immune compartment with the HIV-specific AIM assay and a 45-color spectral flow cytometry panel in the first year after ART initiation. Findings Although proviral DNA decreased during the first year of ART, the inducible reservoir remained stable. One year after ART initiation, exhausted CD8+ T cell abundance correlated significantly with CD4+ T cell count pre-ART. PWH with a late diagnosis had a significantly higher inducible reservoir and lower CD4+ T-cell counts than the non-late HIV diagnosis subgroup. Moreover, the subgroup with a late diagnosis showed higher abundance of exhausted CD8+ T cells, higher expression of activation/exhaustion markers, and lower naive CD4+ T-cell abundance than the non-late diagnosis subgroup. Interpretation Our results show that late diagnosis is associated with a persistently higher inducible viral reservoir and impaired immune recovery. These findings underline the importance of early diagnosis and treatment, and rationalize the use of late diagnosis as a covariate in future cure and reservoir studies.

immunology↗

bioRxiv2025

Global Hypomethylation in Cell-free DNA Enables Non-invasive Colorectal Cancer Screening: Results from a Retrospective Validation Study

Global DNA hypomethylation is a defining hallmark of colorectal cancer (CRC) but is poorly captured by existing cell-free DNA (cfDNA) technologies, which typically interrogate only a fraction of CpG sites and are biased toward CpG islands. We developed Asima Rev, an electrical-impedance cfDNA assay that can differentiate healthy individuals from those with cancer by measuring cfDNA aggregation patterns associated with methylation state, enabling functional detection of genome-wide hypomethylation. In a cohort of 46 treatment-naive CRC patients and 33 controls, Asima Rev achieved 96% sensitivity and 94% specificity, with longitudinal monitoring in six patients fully concordant with clinical outcomes. Interrogation of 11 public methylation array datasets showed that whole array analyses underestimate global changes. However, restricting analyses to OpenSea regions, where cfDNA is enriched, revealed patterns consistent with Asima Rev and a significant 5.8% global hypomethylation in CRC tissue compared to adjacent normal tissue. Hypomethylation was not observed in immune cell genomic DNA (gDNA), a major contributor to cfDNA, supporting a predominantly tumor-derived contribution to the observed cfDNA signal. Together, these results demonstrate that Asima Rev captures a cfDNA signal consistent with true global methylation loss and outperforms locus-specific assays by measuring structural consequences of pan-genomic epigenetic alterations.

bioinformatics↗

bioRxiv2025

Attcatvgg-Net: an Explainable Multioutput Deep Learning Framework for Cataract Stage Classification and Visual Acuity Regression using Multicolor Fundus Images

PurposeThe purpose of this study is to develop and evaluate an attention-guided deep learning model using the multicolor imaging module of Spectralis Optical Coherence Tomography (OCT) imaging for automated cataract severity classification and Visual Acuity (VA) prediction. MethodsWe analyzed 314 multicolor fundus images from 169 patients. Images were preprocessed using an enhanced Retinex algorithm and segmented into three concentric macular zones: Zone 1 (fovea, central 1.5 mm diameter), Zone 2 (parafovea, 1.5-2.5 mm ring), and Zone 3 (perifovea, >2.5 mm radius). A multi-output convolutional neural network (AttCatVgg-Net), based on VGG-16 and enhanced with a Convolutional Block Attention Module (CBAM), was trained to simultaneously perform three-class cataract classification (normal to mild, moderate, severe) and visual acuity (VA) regression. Model performance was assessed using accuracy, AUC, F1-score, and regression metrics. Statistical analyses included the Wilcoxon signed-rank test and the Spearman correlation test. ResultsFor cataract grading, the integrated model using all wavelengths and zones achieved 92.5% accuracy, 94.7% area under the ROC curve (AUC), and a 92.1% F1-score. The green channel alone achieved 90.1% accuracy and 0.93 AUC, while the red channel yielded lower performance (76.3% accuracy, 0.83 AUC). Among anatomical zones, Zone 1 (fovea) and Zone 3 achieved 84.3% and 84.71% accuracy and 0.88 and 0.89 AUC, respectively, whereas Zone 2 underperformed (60.41% accuracy, 0.71 AUC). For visual acuity prediction, the full model achieved a mean absolute error (MAE) of 0.1181 and a coefficient of determination (R-squared) of 0.7759. The green channel demonstrated the strongest correlation with actual VA (correlation coefficient = 0.823, p < 0.001), followed by green-red (0.817) and blue (0.809). The green channel also achieved the lowest Mean Squared Error (MSE = 0.0369) and Root Mean Square Error (RMSE = 0.1920), outperforming other channels. ConclusionsAttention-guided deep learning applied to Spectralis OCT multicolor imaging enables accurate, objective classification of cataract severity and estimation of cataract-related visual acuity loss.

bioengineering↗

bioRxiv2025

RPEGENE-Net: A Multi-Resolution Deep Learning Framework for Predicting Gene Expression from Microscopy Images of Retinal Pigment Epithelium (RPE) Cells

PurposeTo develop a deep learning framework, RPEGENE-Net, capable of predicting gene expression profiles of retinal pigment epithelium (RPE) cells using live-cell microscopy images. MethodsA dataset of live-cell images of RPE cells, treated with various drug regimens and captured at magnifications of 40x, 100x, 200x, and 400x, was used. Gene expression of six key genes involved in epithelial-mesenchymal transition or EMT (including -SMA, ZEB1, TGF-{beta}, CD90, {beta}-catenin, Snail) and treatment classes (Aflibercept, Bevacizumab, Dexamethasone, Aflibercept + Dexamethasone, and untreated control) were analyzed. After preprocessing the image data and gene expression values, we trained and evaluated twelve state-of-the-art deep learning architectures, including three variants of DenseNet, five variants of ResNet, EfficientNet_b5, Inception_v3, RegNet_y_400mf, and a vision transformer model (Swin_b). A two-stage pipeline was implemented, combining autoencoder-based pretraining to extract meaningful features with fine-tuning specifically optimized for gene expression regression and treatment type classification tasks. Features extracted from the second stage across four magnifications were concatenated to generate the final prediction, leveraging multi-scale morphological information for improved accuracy. ResultsDenseNet121 demonstrated superior performance, achieving the highest Pearson correlation coefficients for four genes: -SMA (0.79), ZEB1(0.84), TGF-{beta} (0.83), and Snail (0.86). ResNet34 outperformed other models for CD90 (0.87) and {beta}-catenin (0.85) predictions. The average mean absolute error (MAE) and average root mean square error (RMSE) on test dataset were 0.0244 and 0.1228, respectively. The R2 scores ranged from 0.50 (-SMA) to 0.74 (TGF-{beta}), indicating strong alignment between predicted and actual gene expression values. A multi-level approach, combining data from 40x, 100x, 200x, and 400x magnifications yielded higher R2 scores for almost all genes compared to single-magnification models. For the classification task, DenseNet121 achieved F1 score, precision, recall, and accuracy of 0.98, with a specificity of 0.99. ConclusionsRPEGENE-Net provides a simple, cost-effective method to predict gene expression from live-cell images, with potential applications in experimental studies, RPE transplantation quality control, and broader cell-based research. Multi-magnification imaging enhances model performance, supporting its utility as a scalable tool for diverse gene expression studies.

bioengineering↗

bioRxiv2024

Integrative analysis of patient-derived tumoroids and ex vivo organoid modeling of ARID1A loss in bladder cancer reveals therapeutic molecular targets

Somatic mutations in ARID1A (AT-rich interactive domain-containing protein 1A) are present in approximately 25% of bladder cancers (BC) and are associated with poor prognosis. With a view to discover effective treatment options for ARID1A-deficient BC patients, we set out to identify targetable effectors dysregulated consequent to ARID1A deficiency. Integrative analyses of ARID1A depletion in normal organoids and data mining in publicly available datasets revealed upregulation of DNA repair and cell cycle-associated genes consequent to loss of ARID1A and identified CHEK1 (Checkpoint kinase 1) and chromosomal passenger complex member BIRC5 (Baculoviral IAP Repeat Containing 5) as therapeutically drug-able candidate molecular effectors. Ex vivo treatment of patient-derived BC tumoroids with clinically advanced small molecule inhibitors targeting CHEK1 or BIRC5 was associated with increased DNA damage signalling and apoptosis, and selectively induced cell death in tumoroids lacking ARID1A protein expression. Thus, integrating public datasets with patient-derived organoid modelling and ex-vivo drug testing can uncover key molecular effectors and mechanisms of oncogenic transformation, potentially leading to novel therapeutic strategies. Our data point to ARID1A protein expression as a suitable candidate biomarker for the selection of BC patients responsive to therapies targeting BIRC5 and CHEK1.

cancer biology↗

bioRxiv2024

Development of a latency model based on HIV-1 subtype C to study how long terminal repeat genetic variation impacts viral persistence and latency reversal

Most people living with HIV (PLWH) reside in sub-Saharan Africa. South Africa is the epicentre where 98% of HIV-1 infections are subtype C. However, partially due to unavailability of non-subtype B latency models, most studies of HIV-1 latency and cure have focused on HIV-1 subtype B (HIV-1B) which predominates Europe and USA. Moreover, the effect of inter- and intra-subtype genetic variation of the viral promoter, long terminal repeat (LTR), from PLWH on latency reversal is unknown. We constructed a retroviral vector expressing green fluorescent protein and HIV-1 subtype C (HIV-1C) consensus Tat protein under the control of either HIV-1C consensus or PLWH-derived transmitted/founder (T/F) LTR, produced respective LTR pseudotyped viruses, infected Jurkat E6 and primary CD4+ T cells in vitro, enriched for latently infected cells, and treated these cells with different latency reversing agents. We show that the HIV-1C LTR exhibited lower reactivation compared to HIV-1B. Furthermore, HIV-1C T/F LTR pseudotyped proviral variants with four NF-{kappa}B motifs exhibited lower reactivation compared to those with three NF-{kappa}B motifs. Our data indicate that inter- and intra-subtype HIV-1 LTR genetic variation in combination with host variation modulates latency reversal. Author summaryAntiretroviral therapy (ART) suppresses HIV-1 replication, but it is not curative due to a persistent latent reservoir established early in infection. Although HIV-1 subtype C (HIV-1C) is responsible for about 50% of global and 98% of southern Africa infections, it is underrepresented in HIV-1 cure studies. The unavailability of non-subtype B latency models has led to most studies on HIV-1 latency and cure focusing on HIV-1 subtype B (HIV-1B) which predominates in western countries. The viral promoter, long terminal repeat (LTR) drives viral gene transcription and is important for the HIV-1 life cycle. In this study we undertook to develop a latency model based on HIV-1 subtype C to investigate the effect of inter- and intra- LTR genetic variation on viral persistence and latency reversal. Our data show that the HIV-1C LTR exhibited lower reactivation compared to HIV-1B. Furthermore, HIV-1C T/F LTR pseudotyped proviral variants with four NF-{kappa}B motifs exhibited lower reactivation compared to those with three NF-{kappa}B motifs. Taken together, our data suggest that inter- and intra-subtype HIV-1 LTR genetic variation in combination with host variation modulates latency reversal.

molecular biology↗

bioRxiv2023

PCID2 dysregulates transcription and viral RNA processing to promote HIV-1 latency

HIV-1 latency results from tightly regulated molecular processes that act at distinct steps of HIV-1 gene expression. To elucidate the molecular players that govern latency, we previously performed a dCas9-chromatin immunoprecipitation coupled with mass spectrometry (Catchet-MS) and identified the interactome of the latent HIV-1 LTR. Here we characterize the Catchet-MS-identified PCI domain-containing 2 (PCID2) protein, a component of the TREX2 complex, to play a dual role in promoting HIV-1 latency by enforcing both transcriptional repression and post-transcriptional blocks to HIV-1 gene expression. PCID2 bound the latent HIV-1 LTR and repressed transcription initiation during latency. Depletion of PCID2 remodelled the chromatin landscape at the HIV-1 promoter and resulted in transcriptional activation and reversal of latency. Immunoprecipitation coupled to Mass Spectrometry identified PCID2-interacting proteins to include members of the spliceosome, including negative viral RNA (vRNA) alternative splicing regulators, and PCID2 depletion resulted in over-splicing of intron-containing vRNA and misregulated expression of vRNA splice variants. We demonstrate that MCM3AP and DSS1, two other RNA-binding TREX2 complex subunits that comprise the dock of the complex also inhibit transcription initiation and viral RNA alternative splicing during latency and similarly to PCID2 function as prominent latency associated repressors of HIV-1 gene expression. Thus, PCID2 is a novel HIV-1 latency-promoting factor, which in context of the TREX2 sub-complex PCID2-DSS1-MCM3AP blocks transcription and dysregulates vRNA processing.

microbiology↗

bioRxiv2023

SQuHIVLa: A novel assay for Specific Quantification of inducible HIV-1 reservoir by LAMP

Strategies toward HIV-1 cure aim to clear, inactivate, reduce or immunologically control the virus from a pool of latently infected cells such that combination antiretroviral therapy (cART) can be safely interrupted. In order to assess the impact of any putative curative interventions on the size and inducibility of the latent HIV-1 reservoir, robust and scalable assays are needed to precisely quantify the frequency of infected cells containing inducible replication competent HIV-1. Here, we present Specific Quantification of Inducible HIV-1 by LAMP (SQuHIVLa), a novel assay that leverages the high sensitivity and specificity of RT-LAMP, performed in a single reaction, to detect and quantify cells expressing Tat/Rev msRNA upon activation. Our LAMP primer/probe design exclusively detects subtype-specific HIV-1 Tat/Rev msRNA and exhibits high sensitivity, specificity, and reproducibility. Using SQuHIVLa we quantified the inducible viral reservoir in CD4+ T cells from a diverse group of people living with HIV-1 subtypes B and C on cART. SQuHIVLa presents a high throughput, scalable and specific HIV-1 reservoir quantification tool that is amenable to resource limited settings.

microbiology↗

bioRxiv2021

Hepatitis C Virus Infects and Perturbs Liver Stem Cells

Hepatitis C virus (HCV) is the leading cause of death from liver disease. How HCV infection causes lasting liver damage and increases cancer risk beyond viral clearance remains unclear. We identify bipotent liver stem cells as novel targets for HCV infection, and their erroneous differentiation as the potential cause of impaired liver regeneration and cancer development. We show 3D organoids generated from liver stem cells from actively HCV-infected individuals carry replicating virus and maintain low-grade infection over months. Organoids can be infected with a primary HCV isolate. Virus-inclusive single-cell RNA-sequencing uncovered extensive transcriptional reprogramming in HCV+ cells supporting hepatocytic differentiation, cancer stem cell development and viral replication while stem cell proliferation and interferon signaling are disrupted. Our data adds a pathogenesis factor - infection of liver stem cells - to the biology of HCV infection that explains persistent liver damage and enhanced cancer risk through an altered stem cell state.

microbiology↗

bioRxiv2021

Segmentation of Pancreatic Ductal Adenocarcinoma (PDAC) and surrounding vessels in CT images using deep convolutional neural networks and Texture Descriptors

Fully automated and volumetric segmentation of critical tumors may play a crucial role in diagnosis and surgical planning. One of the most challenging tumor segmentation tasks is localization of Pancreatic Ductal Adenocarcinoma (PDAC). Exclusive application of conventional methods does not appear promising. Deep learning approaches has achieved great success in the computer aided diagnosis, especially in biomedical image segmentation. This paper introduces a framework based on convolutional neural network (CNN) for segmentation of PDAC mass and surrounding vessels in CT images by incorporating powerful classic features, as well. First, a 3D-CNN architecture is used to localize the pancreas region from the whole CT volume using 3D Local Binary Pattern (LBP) map of the original image. Segmentation of PDAC mass is subsequently performed using 2D attention U-Net and Texture Attention U-Net (TAU-Net). TAU-Net is introduced by fusion of dense Scale-Invariant Feature Transform (SIFT) and LBP descriptors into the attention U-Net. An ensemble model is then used to cumulate the advantages of both networks using a 3D-CNN. In addition, to reduce the effects of imbalanced data, a new loss function is proposed as a weighted combination of three classic losses including Generalized Dice Loss (GDL), Weighted Pixel-Wise Cross Entropy loss (WPCE) and boundary loss. Due to insufficient sample size for vessel segmentation, we used the above-mentioned pre-trained networks and fin-tuned them. Experimental results show that the proposed method improves the Dice score for PDAC mass segmentation in portal-venous phase by 7.52% compared to state-of-the-art methods (from 53.08% to 60.6%) in term of DSC. Besides, three dimensional visualization of the tumor and surrounding vessels can facilitate the evaluation of PDAC treatment response.

bioengineering↗

bioRxiv2021

dCas9 targeted chromatin and histone enrichmentfor mass spectrometry (Catchet-MS) identifies IKZF1as a novel drug-able target for HIV-1 latency reversal

A major pharmacological strategy toward HIV cure aims to reverse latency in infected cells as a first step leading to their elimination. While the unbiased identification of molecular targets physically associated with the latent HIV-1 provirus would be highly valuable to unravel the molecular determinants of HIV-1 transcriptional repression and latency reversal, due to technical limitations, this has not been possible. Here we use a dCas9 targeted chromatin and histone enrichment strategy coupled to mass spectrometry (Catchet-MS) to describe the protein composition of the latent and activated HIV-1 5LTR. Catchet-MS identified known and novel latent 5LTR-associated host factors. Among these, IKZF1 is a novel HIV-1 transcriptional repressor, required for Polycomb Repressive Complex 2 recruitment to the LTR. We find the clinically advanced thalidomide analogue iberdomide, and the FDA approved analogues lenalidomide and pomalidomide, to be novel LRAs that, by targeting IKZF1 for degradation, reverse HIV-1 latency in CD4+T-cells isolated from virally suppressed people living with HIV-1. One Sentence SummarydCas9 targeted chromatin and histone enrichment for mass spectrometry (Catchet-MS) led to the identification of IKZF1-targeting thalidomide analogues as novel HIV-1 latency reversal agents

molecular biology↗

bioRxiv2021

A two-color haploid genetic screen identifies novel host factors involved in HIV latency

To identify novel host factors as putative targets to reverse HIV latency, we performed an insertional mutagenesis genetic screen in a latently HIV-1-infected pseudo-haploid KBM7 cell line (Hap-Lat). Following mutagenesis, insertions were mapped to the genome and bioinformatic analysis resulted in the identification of 69 candidate host genes involved in maintaining HIV-1 latency. A select set of candidate genes was functionally validated using shRNA mediated depletion in latent HIV-1 infected J-Lat A2 and 11.1 T cell lines. We confirmed ADK, CHD9, CMSS1, EVI2B, EXOSC8, FAM19A, GRIK5, IRF2BP2, NF1, and USP15 as novel host factors involved in the maintenance of HIV latency. Chromatin immunoprecipitation assays indicated that CHD9, a Chromodomain Helicase DNA-binding protein, maintains HIV latency via direct association with the HIV 5LTR, and its depletion results in increased histone acetylation at the HIV-1 promoter, concomitant with HIV-1 latency reversal. FDA-approved inhibitors 5-Iodotubercidin, Trametinib, and Topiramate, targeting ADK, NF1, and GRIK5, respectively were characterized for their latency reversal potential. While 5-Iodotubercidin exhibited significant cytotoxicity in both J-Lat and primary CD4+ T cells, Trametinib reversed latency in J-Lat cells but not in latently HIV-1-infected primary CD4+ T cells. Crucially, Topiramate reversed latency in cell-line models and latently infected primary CD4+ T cells, without inducing T cell activation or significant toxicity. Thus, using an adaptation of a haploid forward genetic screen, we identified novel and druggable host factors contributing to HIV-1 latency. ImportanceA reservoir of latent HIV-1-infected cells persists in the presence of combination antiretroviral therapy (cART), representing a major obstacle for viral eradication. Reactivation of the latent HIV-1 provirus is part of curative strategies which aim to promote clearance of the infected cells. Using a two-color haploid screen, we identified 69 candidate genes as latency maintaining host factors and functionally validated a subset of 10 of those in additional T-cell based cell line models of HIV-1 latency. We further demonstrated that CHD9 is associated with HIV-1s promoter, the 5LTR while this association is lost upon reactivation. Additionally, we characterized the latency reversal potential of FDA compounds targeting ADK, NF1, and GRIK5 and identify the GRIK5 inhibitor Topiramate as a viable latency reversal agent with clinical potential.

molecular biology↗

bioRxiv2020

Induction of selective cell death in HIV-1-infected cells by DDX3 inhibitors leads to depletion of the inducible reservoir

An innovative approach to eliminate HIV-1-infected cells emerging out of latency, the major hurdle to HIV-1 cure, is to pharmacologically reactivate viral expression and concomitantly trigger intracellular pro-apoptotic pathways in order to selectively induce cell death (ICD) of infected cells, without reliance on the extracellular immune system. In this work we demonstrate the effect of DEAD-box polypeptide 3, X-Linked (DDX3) inhibitors on selectively inducing cell death in latent HIV-1-infected cell lines, primary CD4+ T cells and in CD4+ T cells from cART-suppressed people living with HIV-1 (PLWHIV). RNA sequencing analysis revealed that while overall gene expression was minimally dysregulated, DDX3 inhibition in independent donor CD4+ T cells led to significant downregulation of BIRC5 and HSPB1A, genes critical to cell survival during HIV-1 infection. We used single-cell FISH-Flow technology to characterise latency reversal and the contribution of viral RNA to inducing cell death; pharmacological targeting of DDX3 induced HIV-1 RNA expression, resulting in phosphorylation of IRF3, upregulation of IFN{beta} and selective induction of apoptosis in viral RNA-expressing CD4+ T cells from PLWHIV but not bystander cells. DDX3 inhibitor treatment of CD4+ T cells from PLWHIV in an in vitro culture model over five days resulted in an approximately 50% reduction of the inducible latent HIV-1 reservoir as determined by quantitation of CA HIV-1 RNA, by TILDA, as well as by FISH-Flow technology. Our data support the translation of DDX3 inhibitor class compounds into HIV-1 curative strategies and provide proof of concept for pharmacological reversal of latency coupled to induction of apoptosis towards elimination of the inducible reservoir.

microbiology↗

bioRxiv2019

Gliotoxin, identified from a screen of fungal metabolites, disrupts 7SK snRNP, releases P-TEFb and reverses HIV-1 latency

A leading pharmacological strategy towards HIV cure requires "shock" or activation of HIV gene expression in latently infected cells with Latency Reversal Agents (LRAs) followed by their subsequent clearance. In a screen for novel LRAs we used fungal secondary metabolites (extrolites) as a source of bio-active molecules. Using orthogonal mass spectrometry (MS) coupled to latency reversal bioassays, we identified gliotoxin (GTX) as a novel LRA. GTX significantly induced HIV-1 gene expression in latent ex vivo infected primary cells and in CD4+ T cells from all aviremic HIV-1+ participants. RNA sequencing identified 7SK RNA, the scaffold of the P-TEFb inhibitory 7SK snRNP complex to be significantly reduced upon GTX treatment of independent donor CD4+T cells. GTX disrupted 7SK snRNP, releasing active P-TEFb, which then phosphorylated RNA Pol II CTD, inducing HIV transcription. Our data highlight the power of combining a medium throughput bioassay, mycology and orthogonal mass spectrometry to identify novel potentially therapeutic compounds.

molecular biology↗

bioRxiv2019

Human liver organoids; a patient-derived primary model for HBV Infection and Related Hepatocellular Carcinoma

The molecular events that drive Hepatitis B virus (HBV)-mediated transformation and tumorigenesis have remained largely unclear, due to the absence of a relevant primary model system. Here we propose the use of human liver organoids as a platform for modeling HBV infection and related tumorigenesis. We first describe a primary ex vivo HBV-infection model derived from healthy donor liver organoids after challenge with recombinant virus or HBV-infected patient serum. HBV infected organoids produced cccDNA, expressed intracellular HBV RNA and proteins, and produced infectious HBV. This ex vivo HBV infected primary differentiated hepatocyte organoid platform was amenable to drug screening for both anti-HBV activity as well as for drug-induced toxicity. We also studied HBV replication in transgenically modified organoids; liver organoids exogenously overexpressing the HBV receptor NTCP by lentiviral transduction were not more susceptible to HBV, suggesting the necessity for additional host factors for efficient infection. We also generated transgenic organoids harboring integrated HBV, representing a long-term culture system also suitable for viral production and the study of HBV transcription. Finally, we generated HBV-infected patient-derived liver organoids from non-tumor cirrhotic tissue of explants from liver transplant patients. Interestingly, transcriptomic analysis of patient-derived liver organoids indicated the presence of an aberrant early cancer gene signature, which clustered with the HCC cohort on the TCGA LIHC dataset and away from healthy liver tissue, and may provide invaluable novel biomarkers for disease surveillance and development of HCC in HBV infected patients.

cancer biology↗