Biology subjects

Mahtal, N.

Publications and source records attributed to Mahtal, N..

6 recordsLinked to original sources

bioRxiv2026

Characterization of emerging Oropouche virus tropism and pathogenicity.

BackgroundOropouche virus is an emerging arbovirus increasingly associated with neurological complications, but its human cellular tropism and potential routes to the central nervous system remain poorly defined. This study aimed to characterize infection across clinically relevant human cell types and to investigate interactions with a human blood-brain barrier model and human neuronal/glial cells. MethodsA panel of human cell lines and primary human cells relevant to systemic and neurological disease was infected with Oropouche virus. Viral replication and production of infectious particles were quantified using molecular assays and infectivity titrations, and viral protein expression was assessed by immunoblotting and immunofluorescence. Barrier crossing was evaluated using a Transwell brain endothelial model with permeability monitoring, and infection dynamics in neuronal/glial cultures derived from human neural progenitors were quantified by imaging-based analyses. Group comparisons used non-parametric tests with Dunn-Bonferroni correction and Mann-Whitney tests; neuronal/glial cell counts were analysed using linear models with Fisher tests for interaction terms and multiplicity-adjusted post hoc comparisons. ResultsOropouche virus productively infected hepatocyte-like and intestinal epithelial cells, with high viral RNA output and release of infectious progeny. Primary synoviocytes, chondrocytes and skeletal muscle cells were permissive but produced lower infectious titers. Brain endothelial cells were inoculated and virus was progressively detected in the basolateral compartment, while endothelial permeability remained unchanged, indicating barrier crossing without disruption. In neuronal/glial cultures, both neurons and astrocytes were susceptible; infection was associated with marked cytopathic changes and a preferential, accelerated decline in neuron abundance over time. ConclusionsThese findings demonstrate broad human cell tropism and support blood-brain barrier crossing without major loss of barrier integrity, alongside pronounced neuronal vulnerability. The described models provide a platform to dissect mechanisms of neuroinvasion and to evaluate targeted antiviral strategies.

microbiology↗

bioRxiv2026

Deep learning extracts MoA-specific signatures from high-throughput images of chemically and genetically perturbed Corynebacteria

Tuberculosis (TB) is the worldwide leading infectious killer due to a single pathogen and increasing antimicrobial resistance (AMR) makes it imperative to discover and develop new drugs with novel modes of action (MoAs) to treat TB infections. Phenotypic screening of chemical libraries has proven effective at identifying new compounds against bacterial pathogens. However, a major limitation of standard screens is their inability to uncover the MoA of hits thereby preventing targeted selection of compounds with novel MoAs. Linking drug perturbations to mutants from images could potentially enable to predict the targets of compounds that act through novel MoAs. Here, we develop a deep learning (DL)-based method to screen drug-treated Corynebacterium glutamicum (Cglu), a surrogate model for Mycobacterium tuberculosis (Mtb). Our DL model is based on a convolutional neural network architecture that takes high throughput images as input and is trained to distinguish between different MoAs. We show that our approach can robustly differentiate between the MoAs of established antibiotics and correctly recognise the MoA of antibiotics that were not previously seen by the DL model. We also show that inhibitors with the same and previously unseen MoA cluster together and apart from all other reference drugs, allowing for new MoA discovery. Importantly, we show that our model links images of chemical (drugs) and genetic (mutants) perturbations targeting similar pathways, thus paving the way towards mutant-based target prediction of compounds that act through novel MoAs, directly from high-content images. Finally, we explore the phenotypes induced by genetic disruption of pathways and demonstrate that features extracted with our DL model recover known biological relationships from high-throughput images alone using the cell cycle of Cglu as a case study, a finding with promising potential for fundamental mechanistic studies.

microbiology↗

bioRxiv2025

Intrinsic differences in hamster and mouse macrophage biology correlate with susceptibility to L. donovani infection

The basis for differential susceptibility to Leishmania (L.) donovani infection observed in individuals remains poorly understood. Here we address this important open question comparing bone marrow-derived macrophages from susceptible hamsters (hamBMDMs) and resistant mice (mBMDMs) to identify intrinsic cellular features that may contribute to host-specific outcomes. We first optimized and validated an experimental protocol for generating hamBMDMs, which closely resemble classical mouse BMDMs in terms of morphology, marker gene expression and phagocytic activity. Comparative transcriptomic analysis uncovered rodent-specific, intrinsic differences in the expression of metabolic and immune-related pathways known to influence susceptibility to intracellular Leishmania infection. In vitro infection assays confirmed the microbicidal capacity of hamBMDMs, while also revealing their increased permissiveness to Leishmania proliferation. In conclusion, the combined use of murine and hamster macrophage systems provides a powerful platform to dissect the molecular mechanisms underlying L. donovani survival and host resistance. Our improved protocol allows for the generation of large quantities of functionally validated hamster macrophages, enabling systems-level investigations in this important rodent model that more accurately reflects human infection dynamics than mice. This addresses a major bottleneck in experimental infections with L. donovani, but also other clinically relevant pathogens, such as Mycobacterium spp. and SARS-CoV-2, for which hamsters have been used to model human infection.

pathology↗

bioRxiv2025

Deep learning recognises antibiotic modes of action from brightfield images

Antimicrobial resistance is a growing public health threat predicted to cause up to 10 million deaths a year by 2050. To circumvent existing bacterial resistance mechanisms, discovering antibiotics with novel modes of action (MoAs) is crucial. While growth inhibition assays can robustly identify antibiotic molecules, they miss promising compounds with subinhibitory phenotypes and do not inform on drug MoA. Microscopy-based cytological profiling of drug-treated bacteria with hand-crafted image descriptors or more recently deep learning (DL) provides complementary information on the MoA. However, current approaches are limited by the need for fluorescent labelling and drug exposure at inhibitory concentrations. It also remains unclear if cytological profiling enables the detection of drugs with novel MoAs. Here, we demonstrate an approach based on supervised DL to identify antibiotic drug MoA from microscopy images without fluorescent labelling. We train a convolutional neural network to predict treatment conditions from brightfield images of Escherichia coli exposed to reference drugs covering multiple MoAs. Our method can detect drug exposure at subinhibitory concentrations and distinguishes individual drug treatments with high accuracy (86.2%). The learned representations implicitly capture MoA-specific phenotypes, enabling perfect MoA recognition (100%) without retraining using a model trained on only 644 images. Our approach can identify the MoA of previously unseen drugs with good accuracy (77.8{+/-}3.3%), as long as the MoA is represented by at least one of the training compounds. Finally, we show that our approach can detect if a drug has a novel MoA with an area under the curve above 0.75 for five out of six MoAs, facilitating microscopy-based identification of novel classes of antibiotics. Our methods and results pave the way towards an automated pipeline for antibiotic drug discovery based on imaging and DL.

microbiology↗

bioRxiv2022

Immunometabolic profiling of in vitro and ex vivo Leishmania-infected macrophages (LIMs) reveals unique polarization and bioenergetic signatures

Macrophages are the major host cells of the protozoan parasite Leishmania in mammalian infection. These key innate immune cells display remarkable phenotypic plasticity ranging from pro-inflammatory M1 to anti-inflammatory M2 macrophages that can control infection and tissue homeostasis, respectively. It has been recognized that Leishmania exploits macrophage phenotypic plasticity to establish chronic infection. However, the current notion that these parasites simply trigger an M2-like phenotype seems over-simplified considering the immunopathology observed during leishmaniasis - in particular in response to Leishmania amazonensis - which is often characterized by a mixed Th1/Th2 immune response. Here we combined a series of systems-level analyses to shed new light on the phenotype of Leishmania-infected macrophages (LIMs) during short- and long-term infection, in vitro and in vivo. Immuno-metabolic profiling by RNA-seq, RT-qPCR, cytokine immunoassays, and real-time bioenergetic flux analysis of L. amazonensis-infected bone marrow-derived macrophages (BMDMs) revealed a highly complex and unique phenotypic and bioenergetic signature. In vitro LIMs were characterized by co-expression of both M1 and M2 markers at RNA and protein levels and increased expression of glycolytic genes that matched a progressive metabolic switch from a M2-like respiratory to a M1-like glycolytic energy production observed for both long-term in vitro and in vivo infected macrophages. Unlike in M1 macrophages, glycolytic gene expression did not correlate with increased expression of its key regulatory HIF-1. In contrast, siRNA knock down experiments in primary BMDMs uncovered an essential role of the m6A reader protein IGF2BP2 in stabilizing m6A modified transcripts of the glycolytic pathway, contributing to HIF-1-independent induction of glycolysis. In conclusion, L. amazonensis establishes a complex and unique phenotypic shift in infected macrophages in vitro and in vivo that combines M1-like and M2-like immuno-metabolomic characteristics and implicates differential mRNA stability in induction of aerobic glycolysis. Our data thus uncover epi-transcriptomic regulation as a novel target for Leishmania immune subversion to establish a host cell phenotype beneficial for intracellular parasite development and chronic infection.

immunology↗

bioRxiv2021

A screening pipeline identifies a broad-spectrum inhibitor of bacterial AB toxins with cross protection against influenza A virus H1N1 and SARS-CoV-2

A challenge for the development of host-targeted anti-infectives against a large spectrum of AB-like toxin-producing bacteria encompasses the identification of chemical compounds corrupting toxin transport through both endolysosomal and retrograde pathways. Here, we performed a high-throughput screening of small chemical compounds blocking active Rac1 proteasomal degradation triggered by the Cytotoxic Necrotizing Factor-1 (CNF1) toxin, followed by orthogonal screens against two AB toxins hijacking defined endolysosomal (Diphtheria toxin) or retrograde (Shiga-like toxin 1) pathways to intoxicate cells. This led to the identification of the molecule N-(3,3-diphenylpropyl)-1-propyl-4-piperidinamine, referred to as C910. This compound induces the swelling of EEA1-positive early endosomes, in absence of PIKfyve kinase inhibition, and disturbs the trafficking of CNF1 and the B-subunit of Shiga toxin along the endolysosomal or retrograde pathways, respectively. Together, we show that C910 protects cells against 8 bacterial AB toxins including large clostridial glucosylating toxins from Clostridium difficile. Of interest, C910 also reduced viral infection in vitro including influenza A virus subtype H1N1 and SARS-CoV-2. Moreover, parenteral administration of C910 to the mice resulted in its accumulation in lung tissues and reduced lethal influenza infection.

microbiology↗