Biology subjects

Manina, G.

Publications and source records attributed to Manina, G..

4 recordsLinked to original sources

bioRxiv2026

Stress-responsive Mycobacterium tuberculosis subpopulations manipulate macrophage polarization and can be targeted to limit inflammation

Tuberculosis is characterized by broad clinical heterogeneity that hinders infection control, with differences in lesion development, progression, and treatment outcomes. This complexity is likely associated with Mycobacterium tuberculosis inherent phenotypic variation and its capacity to diversify under host microenvironmental and antimicrobial stressors. Here, we analyze M. tuberculosis at the single-cell and subpopulation level using fluorescent reporters, imaging, transcriptomic, and functional assays. We identify RNA signatures specific to stress-responsive bacilli with translational potential. Focusing on the clinically validated chaperone GroEL2, we find that it correlates with M. tuberculosis growth rate and stress tolerance in vitro and intracellularly. Furthermore, GroEL2 phenotypic diversity influences innate responses in macrophages, which experience different polarization, in turn affecting GroEL2 expression. We also show that targeting GroEL2 impairs pathogen survival and dampens inflammation. This study provides a link between pathogen phenotypic variation and macrophage fates, with implications for early infection outcomes, local disease progression, and subpopulation-targeted interventions.

microbiology↗

bioRxiv2026

Automated Optimization of Bacterial Tracking Pipelines with TrackMate 8

Quantitative analysis of bacterial dynamics in time-lapse microscopy requires robust tracking pipelines, yet selecting and optimizing algorithms for specific experiments remains challenging. Indeed, Microbiologists are confronted with numerous algorithms that must be carefully chosen and parameterized to achieve optimal tracking for their experiments. We present an automated methodology to determine optimal tracking configurations for microbiological applications. It is based on TrackMate 8, a novel version of the TrackMate Fiji plugin extended with microbiology-specific tools. Our approach systematically evaluates algorithm-parameter combinations optimizing biologically relevant metrics (e.g., cell-cycle accuracy, bacteria morphology) and includes: (1) integration of deep-learning algorithms (Omnipose, YOLO, Trackastra) adequate for bacteria images in TrackMate, (2) a TrackMate-Helper extension for parameter optimization, and (3) a tracking and segmentation editor for tracking ground-truth generation. We demonstrate the effectiveness of the methodology on two use cases showing its adaptability to diverse experimental conditions. This methodology enables microbiologists with a widely applicable, automated framework to optimize tracking pipelines, facilitating quantitative analysis in bacterial imaging.

microbiology↗

bioRxiv2023

Dynamic microfluidic single-cell screening identifies pheno-tuning compounds to potentiate tuberculosis therapy

Drug-recalcitrant infections are a leading global-health concern. Bacterial cells benefit from phenotypic variation, which can suggest effective anti-microbial strategies. However, probing phenotypic variation entails spatiotemporal analysis of individual cells that is technically challenging, and hard to integrate into drug discovery. To address this, we developed a flow-controlled multi-condition microfluidic platform suitable for imaging two-dimensional growth of bacterial cells, compressed inside separate microchambers by a soft hydro-pneumatic membrane. With this platform, we implemented a dynamic single-cell screening for compounds that induce a phenotypic change while decreasing cell-to-cell variation, aiming to undermine the bacterial population, making it more vulnerable to other drugs. We first applied this strategy to mycobacteria, as tuberculosis poses a major public-health threat. Our top hit impairs Mycobacterium tuberculosis via a peculiar mode of action and enhances other anti-tubercular drugs. This work proves that pheno-tuning compounds represent a successful approach to tackle pathogens that are increasingly difficult to treat.

microbiology↗

bioRxiv2022

Dynamics of drug response in single mycobacterial cells by microfluidic dose-response assay

Preclinical analysis of drug efficacy is critical for drug development. However, conventional bulk-cell assays statically assess the mean population behavior, lacking resolution on drugescaping cells. Inaccurate estimation of efficacy can lead to overestimation of compounds, whose efficacy will not be confirmed in the clinic, or lead to rejection of valuable candidates. Time-lapse microfluidic microscopy is a powerful approach to characterize drugs at high spatiotemporal resolution, but hard to apply on a large scale. Here we report the development of a microfluidic platform based on a pneumatic operating principle, which is scalable and compatible with long-term live-cell imaging and with simultaneous analysis of different drug concentrations. We tested the platform with mycobacterial cells, including the tubercular pathogen, providing the first proof of concept of a single-cell dose-response assay. This dynamic in-vitro model will prove useful to probe the fate of drug-stressed cells, providing improved predictions of drug efficacy in the clinic.

microbiology↗