Biology subjects

Migliavacca, M.

Publications and source records attributed to Migliavacca, M..

6 recordsLinked to original sources

bioRxiv2026

A bioprinted silk marrow niche reveals mechanical regulation of human megakaryopoiesis under genotoxic stress

Hematopoietic stem and progenitor cells (HSPCs) reside in a mechanically distinct bone marrow niche, yet how niche biomechanics shape genome stability and stress responses has been difficult to test because conventional two-dimensional (2D) culture lacks marrow viscoelasticity and uses surfaces that activate platelets, confounding hematopoietic readouts. Here, we show that this methodological gap has masked a basic principle: the marrow niche actively constrains genotoxic stress signaling in HSPCs, and 2D culture systematically overstates DNA damage and impairs differentiation in vitro. We engineered silk fibroin, a biologically inert biomaterial that does not activate platelets and recapitulates marrow viscoelasticity, into SilkInk, a 3D-bioprintable bioink, and used it to reconstruct a biomimetic marrow microenvironment. HSPCs encapsulated in SilkInk preserved clonogenic potential and multilineage differentiation, whereas 2D-cultured HSPCs activated cytoskeletal-tension and genome-surveillance programs characteristic of chronic stress, including pathways related to replication stress, DNA damage response, and redox stress. Cell phenotyping and single-cell RNA sequencing during megakaryopoiesis revealed that SilkInk supported coordinated endomitotic progression and terminal maturation, with progression from CD34+CD61-CD41-CD42b- progenitors to CD34-CD61+CD41+CD42b+ megakaryocytes, including increased 8N and >16N populations, whereas 2D culture and conventional 3D hydrogels sustained DNA damage signaling and impaired thrombopoiesis. The same hierarchy held under cytotoxic challenge, as 5-fluorouracil amplified DNA damage and crippled platelet output in 2D, whereas SilkInk-encapsulated HSPCs maintained differentiation, mirroring native marrow resilience. These findings reposition niche mechanics as an active determinant of hematopoietic genome stability and establish SilkInk as a physiologically faithful platform for studying hematopoiesis and predicting marrow responses to chemotherapy.

Cell Biology↗

bioRxiv2026

Extracellular Vesicles from Senescent Tumor Cells Are Necessary and Sufficient to Drive Paracrine Senescence

Cellular senescence exerts powerful non-cell autonomous effects through the senescencelzlassociated secretory phenotype (SASP). This SASP comprises soluble factors and extracellular vesicles (EVs). Although soluble SASP components can induce senescence in neigbouring cells, the specific contribution of EVs to paracrine senescence is poorly defined. Here, we show that EVs released by senescent tumor cells are necessary and sufficient to propagate senescence. Conditioned media from bleomycinlzlinduced senescent A549 cells triggered a permanent growth arrest with morphological changes and upregulation of senescence markers in recipient tumor cells. Pharmacological inhibition of EV biogenesis using GW4869 or genetic downregulation of the EV secretion mediator RAB27A markedly attenuates paracrine senescence without affecting soluble SASP factor secretion or the senescent state of producer cells. Proteomic characterization reveals that senescent EVs exhibit a distinct molecular signature enriched for extracellular components and processes related to wound healing and hemostasis. Importantly, purified senescent EVs, devoid of soluble SASP factors, fully recapitulated paracrine senescence induction. These findings identify senescent EVs as key autonomous SASP effectors and highlight vesicular pathways as potential therapeutic targets in cancer and therapylzlinduced senescence.

cancer biology↗

bioRxiv2026

Water Stress Induces Diel Patterns of Root Growth

Growth and death of vegetation control both the amount of carbon held in living biomass and much of the flow between the atmosphere and soils, the largest terrestrial carbon reservoir. However, long-term field datasets on belowground growth dynamics are rare. Knowledge is lacking on how root growth patterns relate to the environment, fluctuating carbon and water availability, and internal plant physiological control, at both seasonal and diel scales. We imaged roots using automated minirhizotrons and interpreting root length density (RLD) automatically twice a day for nine months in a temperate grassland. From winter to autumn, we always observed some root growth in individual images, but with decreasing net RLD (indicative of net turnover) becoming predominant later in the season. Roots grew day-round except during a period of about one month in spring when root growth was only in daytime. This was a period without rain, during which soil moisture depleted rapidly, but not at its driest point. We discuss potential causes for both overall and short-term growth patterns, particularly the change in drivers of growth from internal storage to new photosynthates, or limits imposed by water availability - both soil moisture and rainfall - under shifting environmental conditions.

plant biology↗

bioRxiv2025

Benchmarking remote sensing methods to capture plant functional diversity from space

The development of remote sensing methods to estimate plant functional diversity is limited by mismatches between ecology and remote sensing sampling schemes, and the limited representativeness of local field campaigns. The Biodiversity Observing System Simulation Experiment (BOSSE) provides a modeling framework for benchmarking new methodologies. We used BOSSE to simulate 180 different synthetic "Scenes" encompassing a two-year-long time series of plant trait maps and imagery of hyperspectral reflectance factors, spectral indices, sun-induced chlorophyll fluorescence, land surface temperature, and estimates of plant traits (optical traits). We used these simulations to answer five fundamental, yet unsolved, questions: Q1. How should remote sensing characterize functional diversity in large surfaces (sites)? Diversity metric values saturate with the number of pixels involved, hampering comparisons between plant traits and remote sensing estimates in large areas. The average value of metrics computed over small samples should be used instead. Q2. Which sources of spectral information (or combinations thereof) can best capture plant functional diversity at the site scale? Accounting for background effects is the key. Optical traits (remote sensing estimates of plant traits) are the best estimators for plant functional diversity. Other variables succeed when filtered out of the soil pixels; their combination did not yield additional advantages. Q3. How should remote sensing estimates be validated/compared with plant functional diversity measurements? Leaf area index (LAI) is a better proxy of abundance than the pixel for QRao, but not for variance-based partitioning. It is more sensitive to sample size, but also more resistant to suboptimal spatial resolution. Q4. When (in the phenological year) can remote sensing best capture site-scale plant functional diversity? The estimation error decreased with LAI and stabilized at values above 1 m{superscript 2}/m{superscript 2}. Q5. Which approaches and remote sensing variables are more resistant to the effects of suboptimal spatial resolution? Optical traits, fluorescence, and reflectance factors were the most robust variables. Still, field data resolution needs to be degraded to match the sensors resolution. We found a relative spatial resolution threshold of [~]30 % (where the pixel is around three times larger than the plants). Simulation frameworks like BOSSE enable testing methodologies beyond local contexts and address the current shortage of suitable global datasets, supporting the application and development of methods for assessing plant functional diversity with remote sensing. In the future, BOSSE could contribute to understanding observational results, refining and pre-testing new methodologies, and supporting the development of comparable experimental datasets.

ecology↗

bioRxiv2022

GO WIDE TO GO DEEP: AFFORDABLE, REPLICABLE ROBOTIC MINIRHIZOTRON SAMPLING FOR PHENOLOGY STUDIES

Automating dynamic fine root data collection in the field is a longstanding challenge with multiple applications for co-interpretation and synthesis for ecosystem understanding. High frequency root data are only achievable with paired automated sampling and processing. However, automatic minirhizotron (root camera) instruments are still rare and data is often not collected in natural soils nor analysed at high temporal resolution. Instruments must also be affordable for replication and robust under variable natural conditions. Here, we show a system built with off-the-shelf parts which samples at sub-daily resolution. We paired this with a neural network to analyse all images collected. We performed two mesocosm studies and two field trials alongside ancillary data collection (soil CO2 efflux, temperature and moisture content, and PhenoCam-derived above-ground dynamics. We produce robust daily time-series of root dynamics under all conditions. Temporal root changes were a stronger driver than absolute biomass on soil CO2 efflux in mesocosm. Proximal sensed above ground dynamics and belowground from minirhizotron data were not synchronised. Root properties extracted were sensitive to soil moisture and occasionally to time of day (potentially relating to soil moisture). This may only affect high frequency imagery and should be considered in interpreting such data. HIGHLIGHTCompletely automatic root dynamics with method transferrable between field settings.

ecology↗

bioRxiv2020

senSCOPE: Modeling radiative transfer and biochemical processes in mixed canopies combining green and senescent leaves with SCOPE

Semi-arid grasslands and other ecosystems combine green and senescent leaves featuring different biochemical and optical properties, as well as functional traits. Knowing how these properties vary is necessary to understand the functioning of these ecosystems. However, differences between green and senescent leaves are not considered in recent models representing radiative transfer, heat, water and CO2 exchange such as the Soil-Canopy Observation of Photosynthesis and Energy fluxes (SCOPE). Neglecting the contribution of senescent leaves to the optical and thermal signal of vegetation limits the possibilities to use remote sensing information for studying these ecosystems; as well as neglecting their lack of photosynthetic activity increases uncertainty in the representation of ecosystem fluxes. In this manuscript we present senSCOPE as a step towards a more realistic representation of mixed green and senescent canopies. senSCOPE is a modified version of SCOPE model that describes a canopy combining green and senescent leaves with different properties and function. The model relies on the same numerical solutions than SCOPE, but exploits the linear nature of the scattering coefficients to combine optical properties of both types of leaf. Photosynthesis and transpiration only take place in green leaves; and different green and senescent leaf temperatures are used to close the energy balance. Radiative transfer of sun-induced fluorescence (SIF) and absorptance changes induced by the xanthophyll cycle action are also simulated. senSCOPE is evaluated against SCOPE both using synthetic simulations, forward simulations based on observations in a Mediterranean tree-grass ecosystem, and inverting dataset of ground measurements of reflectance factors, SIF, thermal radiance and gross primary production on a heterogeneous and partly senescent Mediterranean grassland. Results show that senSCOPE outputs vary quite linearly with the fraction of green leaf area, whereas SCOPE does not respond linearly to the effective leaf properties, calculated as the weighted average of green and senescent leaf parameters. Inversion results and pattern-oriented model evaluation show that senSCOPE improves the estimation of some parameters, especially chlorophyll content, with respect SCOPE retrievals during the dry season. Nonetheless, inaccurate knowledge of the optical properties of senescent matter still complicates model inversion. senSCOPE brings new opportunities for the monitoring of canopies mixing green and senescent leaves, and for improving the characterization of the optical properties of senescent material.

ecology↗