Biology subjects

Spagnolo, F.

Publications and source records attributed to Spagnolo, F..

9 recordsLinked to original sources

bioRxiv2025

Comparative analysis of T-cell signatures and astroglial reactivity in Parkinson's pathology across animal models with distinct regenerative capacities

Parkinsons disease (PD) is a progressive neurodegenerative disorder characterized by the selective loss of dopaminergic (DAergic) neurons in the substantia nigra (SN) and the accumulation of misfolded -synuclein (aSyn). Emerging evidence suggests that the immune system, particularly T-cell-mediated responses, plays a key role in the pathogenesis of PD. However, the heterogeneity of these immune responses across species and preclinical models with varying regenerative capacities remains poorly understood. In this study, we performed a comparative analysis of T-cell infiltration, astroglial reactivity, and DAergic neuronal loss across multiple models and species. These included acute DAergic degeneration induced by 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), genetically modified mice with accumulation of aSyn (Thy1-aSyn L61 model), adult zebrafish exposed to MPTP-induced neurotoxicity and human post-mortem midbrain tissue obtained from PD patients. Zebrafish exhibited transient DAergic neurodegeneration followed by neuronal regeneration and a temporary CD4+ T-cell infiltration alongside a regulated astroglial response. In contrast, MPTP-treated mice showed a permanent neuronal loss, increased astrogliosis and CD8+ T-cell infiltration that was negatively correlated with neuronal survival. In contrast, L61 mice exhibited progressive aSyn accumulation with chronic astrogliosis and CD4+ T-cell infiltration not directly linked to neuronal loss. Unlike age-matched controls, the SN from PD brains displayed DAergic degeneration, aSyn aggregation, and elevated CD3+ T-cell infiltration, which correlated with neuronal loss and aSyn burden. These findings emphasise the species- and model-specific immune profiles underlying PD pathology. Our results reveal that CD4+ T-cells contribute to neuronal regeneration following injury in zebrafish. This process is absent in the MPTP and L61 mouse models, which are instead driven by CD8+ or CD4+, respectively. This work underscores the potential of targeted immunomodulation aimed at T cell - glial interactions to slow neurodegeneration and promote repair in PD.

immunology↗

bioRxiv2025

A Chemostat-Based Model for Growing Bacterial Biofilms

Biofilms are groups of microbes that live together in dense communities, often attached to a surface. They play an outsized role in all aspects of microbial life, from chronic infections to biofouling to dental decay. In recent decades, appreciation for the diversity of roles that biofilms play in the environment has grown. Yet, most bacterial studies still rely upon approaches developed in the 19th century and center on planktonic populations alone. Here we present a chemostat-based experimental platform to investigate not only biofilms themselves, but how they interact with their surrounding environments. Our results show that biofilms grow to larger sizes in chemostats as opposed to flasks. In addition, we show that biofilms may be a consistent source of migrants into planktonic populations. We also show that secondary biofilms rapidly develop, although these may be more susceptible to environmental conditions. Taken together, our data suggest that chemostats may be a flexible and insightful platform for the study of biofilms in vitro. IMPORTANCEBiofilms are the predominant way that bacteria live in natural environments and are characterized by three emergent properties: ubiquity, resilience, and impact. They can be found across all environments, both natural and human-made, and across all of recorded time, dating back at least 3.5 billion years. Biofilms also represent a major economic impact of over $5 trillion annually. Yet, most of what is known about bacteria is the result of studies using planktonically growing liquid cultures under laboratory conditions. Here, we propose a comprehensive experimental platform that allows for study of biofilms on the molecular, organismal, and community levels using chemostats.

microbiology↗

bioRxiv2024

Exploiting XAI maps to improve MS lesion segmentation and detection in MRI

To date, several methods have been developed to explain deep learning algorithms for classification tasks. Recently, an adaptation of two of such methods has been proposed to generate instance-level explainable maps in a semantic segmentation scenario, such as multiple sclerosis (MS) lesion segmentation. In the mentioned work, a 3D U-Net was trained and tested for MS lesion segmentation, yielding an F1 score of 0.7006, and a positive predictive value (PPV) of 0.6265. The distribution of values in explainable maps exposed some differences between maps of true and false positive (TP/FP) examples. Inspired by those results, we explore in this paper the use of characteristics of lesion-specific saliency maps to refine segmentation and detection scores. We generate around 21000 maps from as many TP/FP lesions in a batch of 72 patients (training set) and 4868 from the 37 patients in the test set. 93 radiomic features extracted from the first set of maps were used to train a logistic regression model and classify TP versus FP. On the test set, F1 score and PPV were improved by a large margin when compared to the initial model, reaching 0.7450 and 0.7817, with 95% confidence intervals of [0.7358, 0.7547] and [0.7679, 0.7962], respectively. These results suggest that saliency maps can be used to refine prediction scores, boosting a models performances.

bioengineering↗

bioRxiv2023

Bacteriophage therapy for the treatment of Mycobacterium tuberculosis infections in humanized mice

The continuing emergence of new strains of antibiotic-resistant bacteria has renewed interest in phage therapy; however, there has been limited progress in applying phage therapy to multi-drug resistant Mycobacterium tuberculosis (Mtb) infections. In this study, we tested three bacteriophage strains for their Mtb-killing activities and found that two of them efficiently lysed Mtb H37Rv in 7H10 agar plates. However, only phage DS6A efficiently killed H37Rv in liquid culture and in Mtb-infected human primary macrophages. In subsequent experiments, we infected humanized mice with aerosolized H37Rv, then treated these mice with DS6A intravenously to test its in vivo efficacy. We found that DS6A treated mice showed increased body weight and improved pulmonary function relative to control mice. Furthermore, DS6A reduced Mtb load in mouse organs with greater efficacy in the spleen. These results demonstrated the feasibility of developing phage therapy as an effective therapeutic against Mtb infection.

microbiology↗

bioRxiv2022

Risk of Infection Due to Airborne Virus in Classroom Environments Lacking Mechanical Ventilation

The COVID-19 pandemic highlighted the role of indoor environments on disease transmission. Enclosed spaces where pathogen-laden aerosols accumulate was strongly linked to increased transmission events. Here we employ a surrogate non-pathogenic virus, the bacteriophage phi6, to interrogate aerosol transmission in classroom environments that do not have any natural or mechanical ventilation in order to determine how effectively aerosols facilitate new infections. We find that virus-laden aerosols establish new infections over all distances tested within minutes and that the time of exposure did not change transmission rate. We further find that humidity, but not temperature nor a UV-based disinfection device, significantly impacted transmission rates. Our data suggest that, even without mechanical ventilation, relative humidity remains a highly effective mitigation strategy while UV air treatment did not. Practical ImplicationsTransmission of pathogens through airborne particles is a major source of disease transmission. People now spend much of their time indoors, thus understanding indoor airborne transmission is vital to managing outbreaks. Most classrooms in the U.S. do not have any mechanical ventilation systems and so here, we test airborne transmission of a virus in such classrooms. Infection transmission rates are not greatly impacted by distance, time or even some UV treatment, but are curbed by the amount of moisture in the air.

microbiology↗

bioRxiv2022

High-frequency longitudinal white matter diffusion- & myelin-based MRI database: reliability and variability

Assessing the consistency of quantitative MRI measurements is critical for inclusion in longitudinal studies and clinical trials. Intraclass coefficient correlation and coefficient of variation were used to evaluate the different consistency aspects of diffusion- and myelinbased MRI measures. Multi-shell diffusion and inhomogeneous magnetization transfer datasets were collected from twenty healthy adults at a high-frequency of five MRI sessions. The consistency was evaluated across whole bundles and the track-profile along the bundles. The impact of the fiber populations on the consistency was also evaluated using the number of fiber orientations map. For whole and profile bundles, moderate to high reliability of diffusion and myelin measures were observed. We report higher reliability of measures for multiple fiber populations than single. The overall portrait of the most consistent measurements and bundles drawn from a wide range of MRI techniques presented here will be particularly useful for identifying reliable biomarkers capable of detecting, monitoring and predicting white matter changes in clinical applications and has the potential to inform patient-specific treatment strategies. Key pointsO_LIReliability and variability are excellent to good for DWI measurements, and good to moderate for MT measures for whole bundles and along the bundles. C_LIO_LIThe number of fiber populations affects the reliability and variability of the MRI measurements. C_LIO_LIThe reliability and variability of MRI measurements are also bundle dependent. C_LI

neuroscience↗

bioRxiv2021

Humidity Reduces Rapid and Distant Airborne Travel of Viable Viral Particles in Classroom Settings

The transmission of airborne pathogens via aerosols is considered to be the main route through which a number of known and emerging respiratory diseases infect their hosts. It is therefore essential to quantify airborne transmission in closed spaces and determine the recommendations that should be implemented to minimize exposure to pathogens in built environments. We have developed a method to detect viable virus particles from aerosols by using an aerosolized bacteriophage Phi6 in combination with its host Pseudomonas phaseolicola, which when seeded on agar plates acts as a virus detector that can be placed at a range of distances away from an aerosol-generating source. Based on this method we present two striking results. (1) We consistently detected viable phage particles at distances of up to 18 feet away from the source within 15-minutes of exposure in a classroom equipped with a state of the art HVAC system. (2) Increasing the relative humidity beyond 40% significantly reduces dispersal. Our method can be used to quantify the exposure to pathogens at various distances from the source for different amounts of time, data which can be used to set safety standards for room capacity and to ascertain the efficacy of interventions that aim to reduce pathogen levels in closed spaces of specified sizes and intended uses. SummaryWe present a method to experimentally determine the exposure to airborne pathogens in closed spaces.

microbiology↗

bioRxiv2019

Antibiotic Resistance Increases Evolvability and Maximizes Opportunities Across Fitness Landscapes

Antibiotic resistance continues to grow as a public health problem. One of the reasons for this continued growth is that resistance to antibiotics is strongly selected for in the presence of antibiotics and weakly selected against after their removal. This is frequently thought to be due to the effects of compensatory mutations. However, compensatory mutations are often not found in clinically relevant strains of antibiotic resistant pathogens. Here, we conduct experiments in vitro that highlight the role that fine scale differences in environment play in the maintenance of populations after selection for resistance. We show that differences in the mode of growth, dictated by environmental factors, are capable of reliably changing the force and direction of selection. Our results show that antibiotic resistance can increase evolvability in environments if conditions for selection exist, selecting differentially for newly arising variation and moving populations to previously unavailable adaptive peaks.\n\nSignificanceAntibiotic resistant bacteria are a large and growing problem for public health. A major question has been why antibiotic resistant strains do not disappear when they must compete with higher fitness drug sensitive strains. Here we show that selection for antibiotic resistant strains is particularly sensitive to differences in environmental conditions and that these differences help to define the fitness landscapes upon which these populations adapt. The result is an increase in evolvability, with many adaptive peaks that drug resistant populations can explore through natural selection, making predictions of evolution difficult and selection against resistant strains improbable.

evolutionary biology↗

bioRxiv2017

Pathogen Population Structure Can Explain Hospital Outbreaks

ObjectiveTo analyze Hospital Acquired Infection (HAI) outbreaks using microbial population biology dynamics in order to understand outbreaks as a biological system.\n\nDesignComputational modeling study.\n\nMethodsThe majority of HAI transmission models describe dynamics on the level of the host rather than on the level of the pathogens themselves. Accordingly, epidemiologists often cannot complete transmission chains without direct evidence of either host-host contact or large reservoir populations. Here, we propose an ecology-based model to explain the transmission of pathogens in hospitals. The model is based upon metapopulation biology, which describes a group of interacting localized populations and island biogeography, which provides a basis for how pathogens may be moving between locales. Computational simulation trials are used to assess the applicability of the model.\n\nResultsResults indicate that pathogens survive for extended periods without the need for large reservoirs by living in localized ephemeral populations while continuously transmitting pathogens to new seed populations. Computational simulations show small populations spending significant portions of time at sizes too small to be detected by most surveillance protocols. The number and type of these ephemeral populations enable the overall pathogen population to be sustained.\n\nConclusionsBy modeling hospital pathogens as a metapopulation, observations characteristic of hospital acquired infection outbreaks for which there has previously been no sufficient biological explanation, including how and why empirically successful interventions work, can now be accounted for using population dynamic hypotheses. Epidemiological links between temporally isolated outbreaks are explained via pathogen population dynamics and potential outbreak intervention targets are identified.

epidemiology↗