Biology subjects

Pezzotti, M.

Publications and source records attributed to Pezzotti, M..

8 recordsLinked to original sources

bioRxiv2025

LigHTS: Massively Parallel Biomimetic Photo-Functionalization for Imaging-Based Ultra-High-Throughput Screening

Imaging-based ultra-high-throughput screening (UHTS) in pharma and biotech still runs on 384/1536-well plates whose stiff, flat substrates limit biological fidelity and screening efficiency. Highly biomimetic organs-on-chips and organoids improve relevance but lack reproducibility and plate-scale throughput. Biomimetic hydrogel scaffolds can be produced at scale through photopolymerization, which yet uses focused optics to define micrometer-resolved geometries, constraining scalability. To address the technical challenge of truly scalable biomimetic substrates featuring anisotropies, this study presents LigHTS, an all-optical, in-well method that replaces focused with collimated illumination to photofabricate structured hydrogels in standard 384/1536-well plates. Adding food dye tartrazine to gelatin-methacrylate (GelMA) solutions increases hydrogel thickness sensitivity to UV dose by [~]10x, allowing uniform control of film thickness without lenses. Entire plates are functionalized in parallel with soft hydrogels ([~]1-10 kPa) whose thickness is tunable from 10 to 100 {micro}m. Simultaneously, simply interposing film photomasks encoding anisotropies enables orthogonal control of thickness and topography at UHTS throughput. Biological effect is demonstrated with mechanosensitive HT1080 cells, which display stiffness- and topography-dependent spreading and contact-guided migration on LigHTS-produced grooved substrates. Geometric uniformity across the plate (coefficient of variation <20%) meets HTS reproducibility standards, providing a readily available solution with enhanced biomimicry for imaging-based UTHS pipelines.

bioengineering↗

bioRxiv2025

Bioimage analysis for multiplexed FUCCI acquisitions powered by deep learning

The FUCCI sensor fluorescently labels cell cycle phases, which is essential to assess normal and abnormal cell-cycle progression in physiological and pathological conditions of developing organisms. However, accurate cell-cycle decoding is challenging in the low signal-to-noise conditions typical of multiplexed live cell imaging. To address this challenge, we developed deep learning networks that integrate FUCCI signals with a cytoplasmic alpha-tubulin fluorescent reporter. Our approach outperforms existing methods for both segmenting and classifying FUCCI nuclei, even in low signal-to-noise conditions. The resulting high-accuracy segmentation enables robust automated tracking. We leverage this to introduce a dynamic time warping analysis that determines cell cycle pseudotime from incomplete tracks and can detect cell cycle arrest. We provide pre-trained networks for multichannel FUCCI analysis, offering a powerful tool for studies in cancer research, development, and mechanobiology.

bioengineering↗

bioRxiv2025

Vertically Integrated System for Tracking and Assessing cell-cycle aware phenotypes under confinement

Quantitative cell biology often studies migration and the cell-cycle (CC) in separate assays, limiting mechanistic insights, particularly under geometric confinement. Here, we introduce a vertically integrated platform for simultaneously tracking single-cell migration and assessing CC under confinement. Our system integrates cell engineering via multiplexed sensors for cell-cycle, actin, and tubulin, as well as photopatterned engineered extracellular matrix (ECM) islands of defined sizes. It also features an automated, high-throughput pattern-aware imaging pipeline (Fab2Mic) that enables on-pattern, joint migration-CC assessment in the same live cells. Since the local microenvironment plays a critical role in metastasis by constraining cell behaviors within spatial boundaries, we used an HT1080 fibrosarcoma model as an illustrative case. Where static phenotyping yielded 40% G1 and 60% S/G2/M, with larger cell areas and tubulin spread in the S/G2/M phase, dynamic phenotyping via live-cell imaging confirmed CC-linked motility, with faster instantaneous velocities in G1, exemplifying the CC-migration correlations. These phenotypes were modulated by the spatial confinement imposed by the engineered ECM islands. Stronger confinement reduced cell area and tubulin spread and increased the frequency of abnormal CC events, particularly Long G1 states on smaller engineered ECM islands. It also induced a confinement-specific S/G2/M-G1 mitotic slippage, observed only under our confined conditions. Together, this vertically integrated system suggests that confinement may continuously tune migration-CC coupling and provides a deployable pipeline for CC-aware mechanobiology and screening. Moreover, we stress how dynamic imaging provides access to variables that are difficult or impossible to infer from static snapshots, including velocity and CC timing.

bioengineering↗

bioRxiv2025

MicroSplit: Semantic Unmixing of Fluorescent Microscopy Data

Fluorescence microscopy, a key driver for progress in the life sciences, faces limitations due to the microscopes optics, fluorophore chemistry, and photon exposure limits, necessitating trade-offs in imaging speed, resolution, and depth. Here, we introduce Micro[S]plit, a computational multiplexing technique based on deep learning that allows multiple cellular structures to be imaged in a single fluorescent channel and then unmix them by computational means, allowing faster imaging and reduced photon exposure. We show that Micro[S]plit efficiently separates up to four superimposed noisy structures into distinct denoised fluorescent image channels. Furthermore, using Variational Splitting Encoder-Decoder (VSE) networks, our approach can sample diverse predictions from a trained posterior of solutions. The diversity of these samples scales with the uncertainty in a given input, allowing us to estimate the true prediction errors by computing the variability between posterior samples. We demonstrate the robustness of Micro[S]plit networks, which are trained for each splitting task at hand, across various datasets and noise levels and show its utility to image more, to image faster, and to improve downstream analysis. We provide Micro[S]plit along with all associated training and evaluation datasets as open resources, enabling life scientists to immediately benefit from the potential of computational multiplexing and thus help accelerate the rate of their scientific discovery process.

bioinformatics↗

bioRxiv2024

HYDRA: HYdrogel Dispensing with Robotic Automation for high throughput drug testing

Traditional plastic- and glass-based cell culture platforms lack physiological relevance which limits their predictive power in drug development. Organoids and organs-on-chip offer biomimicry in late preclinical stages but lack scalability for high-throughput screening (HTS) in earlier stages. In fact, even introducing the simplest critical biomimetic cue, thin hydrogel layers, into the small wells of HTS plates causes the formation of curved menisci that disrupt cell seeding and imaging. We introduce HYDRA (HYDrogels by Robotic liquid handling Automation), an automated method that enables consistent hydrogel fabrication in HTS plates. We used liquid handling robots to dispense hydrogel precursor solutions and avoid contact with the sidewalls to prevent meniscus formation. We used gelatin for its mild surfactant properties, which allow pinning of the droplets contact line, promoting uniform spread. Finally, we re-aspirated the excess liquid, leaving behind a hydrogel layer with controlled stiffness and thickness. We show compatibility with standard 96- and 384-well plates and integration with existing automated workflows, including quality control. We validated HYDRA in dose-response assays using anti-cancer drugs, genetically engineered epithelial cells, phase holography, and fluorescence microscopy. We believe that HYDRA provides a scalable, biomimetic, and therefore more predictive alternative for early- stage screening and in vitro drug testing.

bioengineering↗

bioRxiv2024

CALIPERS: Cell cycle-aware live imaging for phenotyping experiments and regeneration studies

Cell cycle progression, migration, and proliferation shape development and regeneration, but simultaneous live-cell imaging remains challenging as conventional fluorescent cell cycle indicators (FUCCI) monopolize the green and red channels used by most structural and functional biosensors. To overcome this, we integrated a spectrally re-engineered FUCCI variant, open-source analysis software, and four-color human stem cell reporter lines into CALIPERS: a method for Cell-cycle-Aware Live-cell Imaging in Phenotyping and Regeneration Studies.

bioengineering↗

bioRxiv2022

A molecular phenology scale of fruit development

Fruit growth and development consists of a continuous succession of physical, biochemical, and physiological changes driven by a genetic program that dynamically responds to environmental cues. Establishing recognizable stages over the whole fruit lifetime represents a fundamental requirement for research and fruit crop cultivation. This is especially relevant in perennial crops like the grapevine to scale the development of its fruit across genotypes and growing conditions. In this work, molecular-based information from several grape berry transcriptomic datasets was exploited to build a molecular phenology scale (MPhS) and to map the ontogenic development of the fruit. The proposed statistical pipeline consisted in an unsupervised learning procedure yielding an innovative combination of semiparametric, smoothing and dimensionality reduction tools. The transcriptomic distance between fruit samples was precisely quantified by means of the MPhS that also enabled to highlight the winding dynamics of the transcriptional program over berry development through the calculation of the rate of variation of MPhS stages by time. The MPhS allowed the alignment of time-series fruit samples proving to be a step forward in mapping the progression of grape berry development with higher precision compared to classic time- or phenotype-based approaches and inspiring the use of the transcriptional information to scale the developmental progression of any organ in any plant species.

plant biology↗

bioRxiv2021

Initiation of organ maturation and fruit ripening in grapevine is controlled by the CARPO-NAC transcription factor

Grapevine is a woody temperate perennial plant and one of the most important fruit crops with global relevance in both the fresh fruit and winemaking industries. Unfortunately, global warming is affecting viticulture by altering developmental transitions and fruit maturation processes. In this context, uncovering the molecular mechanisms controlling the onset and progression of ripening could prove essential to maintain high-quality grapes and wines. Through a deep inspection of previously published transcriptomic data we identified the NAC family member VviCARPO (Controlled Adjustment of Ripening and maturation of Plant Organs) as a key regulator of grapevine maturation whose induction precedes the expression of well-known ripening associated genes. We explored VviCARPO binding landscapes through DAP-seq and overlapped its bound genes with transcriptomics datasets from stable and transient VviCARPO overexpressing grapevine plants to define a set of high-confidence targets. Among these, we identified key molecular ripening markers. Physiological, metabolic and promoter activation analyses showed that VviCARPO induces chlorophyll degradation and anthocyanin accumulation through the up-regulation of VviSGR1 and VviMYBA1, respectively, with the latter being up-regulated through a VviCARPO-VviNAC03 regulatory complex. Despite showing a closer phylogenetic relationship to senescent-related AtNAP homologues, VviCARPO complemented the nor mutant phenotype in tomato, suggesting it may have acquired a dual role as an orchestrator of both ripening- and senescence-related processes. Our data supports CARPO as a master regulator of the grapevine vegetative-to-mature phase organ transition and therefore an essential target for insuring fruit quality and environmental resilience. SIGNIFICANT STATEMENTCARPO is a grape NAC transcription factor central to fruit ripening and tissue senescence. This regulator influences multiple biological pathways common to both processes including cell wall metabolism, chlorophyll degradation, pigment production and hormone synthesis/signaling through regulation of their key genes. As various external stresses and changing climatic conditions influence vegetative growth and berry ripening, CARPO could prove a useful genetic and breeding target towards maintaining necessary crop performance and fruit-quality characteristics.

plant biology↗