Biology subjects

Fusco, D.

Publications and source records attributed to Fusco, D..

15 recordsLinked to original sources

bioRxiv2026

AutoWrinkleID: a machine learning pipeline for biofilm wrinkle identification and quantitative analysis

Biofilms are widely distributed in both natural and engineered systems and play a fundamental role in microbial ecology and biotechnological applications. When grown on agar substrates, biofilms often exhibit macroscopic structural features due to mechanical instabilities driven by matrix production. These wrinkles encode relevant information about biofilm growth and structural development and have even been shown to possess some functional roles. Despite their relevance, currently available approaches for wrinkle detection from images rely on manual annotation, which is time-consuming, not scalable, and strongly dependent on the annotator. In the present study, we developed an end-to-end machine learning pipeline, named AutoWrinkleID, that starts from bright field images of biofilms and performs wrinkle identification, characterisation, and quantification across multiple bacterial species and strains. The name reflects the automated identification and subsequent characterisation and quantification of biofilm wrinkles. The annotations used to generate the masks, namely images containing only the wrinkle structures, were obtained both through manual labelling and using constitutive fluorescence and motility fluorescence. Interestingly, we found that models trained using only manual annotations perform worse than those trained using motility fluorescence markers. A comparison between motility and constitutive fluorescence masks further indicates that motility based annotations consistently outperform constitutive fluorescence across all strains, strongly suggesting that motile phenotypes are tightly associated with wrinkle structures. Additional computational analysis is conducted on the same dataset to assess the robustness and limitations of the results as a function of training dataset. We also observed that Sholl analysis, originally developed for the study of neuronal dendrites and later applied to wrinkle analysis, can effectively characterize wrinkle patterns, although its applicability is strongly limited by wrinkle shape and by the quality of the masks.

biophysics↗

bioRxiv2026

Resource availability and dimensionality result in ecology-dependent selection in bacteriophage spatial expansions

In microbial populations, fitness, which is essential to understand and predict evolution, is often defined and measured as the net growth rate of a population in isolation. Applying the same definition to viruses is challenging, both because viral replication involves a host infection process, which is determined by several parameters that are context-dependent, and because viruses compete heavily for resources (susceptible cells). These challenges are particularly exacerbated in spatial range expansions, where multiplicity of infection is often high and resource availability varies in time and space. To assess different fitness definitions and their generalizability, we investigate a model of coupled partial differential equations for phage plaque expansion in one and two dimensions. We find that two commonly used metrics for phage fitness in plaque expansions, i.e., steady state phage densities and front expansion speed in isolation, are unable to reliably predict the winner in one- and two-dimensional direct competitions. More generally, we find that optimal phage traits depend on the dimensionality of the system and the make-up of the phage population, leading to unexpected behaviours, e.g., rock-paper-scissor dynamics and, in high dimensions, enhanced phage density due to the nearby presence of a competitor. We show that the phenomenon stems from the interplay between resource consumption and replication and thus may apply more broadly to any population competing for shared resources.

ecology↗

bioRxiv2026

Co-expression-based models improve eQTL predictions and highlightnovel transcriptome-wide genes associated with schizophrenia

Non-coding genetic variants statistically associated with complex heritability phenotypes are thought to act primarily through transcriptome regulatory mechanisms. Predictions of gene expression in tissue like the human brain traditionally rely primarily on cis-eQTLs. Here, we introduce INGENE and MODULE, trans-eQTLs models designed to enhance the prediction of gene expression by capturing the collective impact of candidate trans-eQTLs acting within co-expression networks. Exploiting RNA-seq data in six post-mortem brain regions (amygdala, caudate nucleus, dorsal/subgenual anterior cingulate cortex, dorsolateral prefrontal cortex, and hippocampus), we validate our models on two testing datasets, demonstrating increased gene predictability compared to both an original cis-based model and to EpiXcan, the leading benchmark in cis-model performance. Integration of cis- and trans-predictions significantly improves gene-level expression imputation (MLE = 0.05) for 18,744 genes across the six brain regions considered. Applying cis and trans models to PGC wave 3 genotypes identifies 766 SCZ-associated genes across brain regions (pFDR < .01), emphasizing the complementary nature of cis and trans predictions in trait association discovery. Of these genes, 641 represent novel transcriptome-wide associations with schizophrenia, highlighting the role of trans-heritability and genetic interactions underlying risk for this disorder, in addition to further supporting 125 previous candidates.

genomics↗

bioRxiv2025

Nanoplasmonic SERS reveals previously uncharacterised indole derivative in E. coli metabolism

Tryptophanase (TnaA) is a promiscuous enzyme which regulates the production of amino acid-derived metabolites, essential for bacterial communication. TnaA is known to convert tryptophan into indole, an important signalling molecule influencing a range of behaviours - from bacterial quorum sensing to urinary tract infections (UTI) - but other conversion routes remain obscure. Here, we show that nanoplasmonic surface-enhanced Raman spectroscopy (SERS) combined with targeted genetic subtraction enables the label-free, cellular characterisation and structural identification of TnaA-derived metabolites directly from Escherichia coli culture solutions, without isolation or purification. We systematically profile the SERS spectra of wild-type and tnaA gene knockout strains (E. coli BW25113 and the uropathogenic 536) supplemented with each of the twenty amino acids, uncovering a previously unreported TnaA-dependent metabolic signature, I*, whose Raman fingerprint does not match free indole or any common indole derivative characterised by mass spectrometry. Using isotopomer-labelled substrates together with structural reference compounds, we perform label-free structural deduction of I* directly from SERS spectra. We find I*s structure is consistent with an intact indole ring carrying a C3 substituent, likely produced indirectly from intracellular tryptophan. These findings introduce a novel indole metabolite, raise new hypotheses regarding the biological role of TnaA-mediated byproducts in bacterial signalling and virulence, and demonstrate that nanoplasmonic SERS provides a powerful framework for probing enzyme activity and bioactive metabolite production directly from living bacterial cultures with nanomolar sensitivity and structural specificity.

microbiology↗

bioRxiv2025

Live and let die: lysis time variability and resource limitation shape lytic bacteriophage fitness

Bacteriophages (phages) play a critical role in controlling bacterial populations, both in nature and as potential therapeutic agents. Their ability to replicate, compete against each other, and eradicate target cell populations is usually understood through a number of life history parameters, traditionally measured by population-level assays, which implicitly average the parameters value across a large number of infection events. Recent experiments suggest that bacteriophage life history parameters are subject to considerable heterogeneity, raising the question of whether experimental and modelling efforts that do not account for this variability may overlook important factors in phages behaviour, competitive fitness or therapeutic viability. Here, using agent-based simulations, we investigate the importance of stochasticity in lysis time and burst size of lytic bacteriophages in two common laboratory competition experiments: serial passage of well-mixed populations and plaque expansion across a bacterial lawn. We find that a phages analytic growth rate in isolation can be a poor predictor of its fitness advantage in simulated competition experiments. Specifically, when lysis times are tightly distributed, we identify a novel effect we name "population resonance", through which a bacteriophage can display a significant fitness advantage over a competitor with a much greater growth rate in isolation. Our simulations also show that both serial passage and plaque expansion reward variability in lysis time more than expected, by increasing the phage resilience when resources are scarce. Author SummaryBacteriophages (viruses that infect bacteria) can be described by a set of attributes called life history parameters. Historically, these parameters could only be measured on-average over large populations. Recent experimental advancements, however, have enabled their quantification at the single-cell-single-virus level, and have revealed that these traits are subject to inherent variability, even for genetically identical viruses infecting genetically identical cells. Here, we explore whether the degree of variability in one particular life history parameter, the lysis time (the time taken for a bacteriophage to infect and kill its host bacteria) might be subject to natural selection, by quantifying its effects on phages fitness in two simulated competition experiments: serial passage and plaque expansion. Surprisingly, we find that lysis time variability is advantageous in competition even when it reduces the phages growth rate in isolation. This finding opens the door to future computational and experimental work, as it demonstrates that mean values alone are not sufficient to describe or predict a bacteriophage efficacy, and that models that ignore this variability can overlook viable evolutionary strategies.

evolutionary biology↗

bioRxiv2024

Ozboneviz: An Australian Precedent in FAIR 3D Imagery and Extended Biodiversity Collections

Billions of specimens are in biodiversity collections worldwide, and this infrastructure is crucial for research on Earths natural history. Three-dimensional (3D) imagery of specimens is an increasingly important part of the Digital Extended Specimen network of metadata. Open access, high fidelity 3D imagery of biodiversity specimens improves researcher efficiency, equity and increases public engagement with collections. We introduce Ozboneviz, an open access collection of FAIR (Findable, Accessible, Interoperable, Reusable) 3D imagery aiming to enhance research capacity in Australasian vertebrate skeletal morphology. Ozboneviz is an Australian test case demonstrating the feasibility of creating multi-institutional, FAIR 3D biodiversity imagery collections. We outline project design, challenges, and use by the international research community. We then discuss the urgent need for investment in infrastructure and curatorial support to progress the digitisation of Australian biodiversity collections in a way that maximises stakeholder benefit and facilitates 3D data discoverability and retrieval.

zoology↗

bioRxiv2024

Electrogenic Dynamics of Biofilm Formation: Correlation Between Genetic Expression and Electrochemical Activity in Bacillus subtilis

Bacterial biofilms are structured microbial communities that play a big role in diverse processes such as nutrient cycling and bacterial pathogenesis. Biofilms are known for their electron transfer properties which are essential for metabolic processes, microbial survival, and maintaining redox balance. In this study, we investigated the electrogenic properties of Bacillus subtilis, a bacterial producer of electron-donating biofilms. Interdigitated gold electrodes were utilized to continuously measure the electrochemical activity of biofilm-forming B. subtilis cells as well as genetic mutants unable to create them (biofilm-deficient), over three days of growth. The formation of extracellular polymeric substances (EPS) and filamentous appendages was monitored via scanning electron microscopy (SEM). Chronoamperometry was used to assess electrochemical activity, which showed fluctuations in electrical current at specific time points in biofilm-forming cells. In contrast, biofilm-deficient cells showed no corresponding changes in current. Cyclic voltammetry (CV) revealed significant differences between the voltammograms of biofilm-forming and biofilm-deficient cells that were hypothesized to be a result of the reduction of secreted flavodoxin only in biofilm-forming cells. Electrochemical impedance spectroscopy (EIS) was also performed at various intervals and analyzed using an equivalent circuit model. We identified the presence of a charge transfer resistance (Rct) exclusively in biofilm-forming cells which correlated to the time of increased electrochemical activity measured using choronoamperometry. Finally, through confocal microscopy, we found that the expression of a gene involved in biofilm matrix formation, tasA, was correlated with the time where electrochemical charge transfer was measured. Altogether, these results indicate that electrochemical activity is primarily present in biofilm-forming cells rather than in biofilm-deficient mutants. By combining electrochemical and microscopic methods, a methodology was developed to continuously monitor the stages of biofilm formation through measurement of electrochemical activity, substantiating a correlation between the expression of biofilm genes and their electrochemical or redox activities. These data show that electrochemical activities within biofilms vary over time and there is a temporal relationship between these processes and the expression of genes responsible for biofilm development.

bioengineering↗

bioRxiv2024

Single-cell imaging of the lytic phage life cycle dissects the timing and noise in individual infection steps

When a lytic bacteriophage infects a bacterial cell, it commandeers the cells resources to replicate, ultimately causing cell lysis and the release of new virions. As phages function as obligate parasites, each stage of the infection process depends on the physiological parameters of the host cell. Given the inherent physiological variability within a population of genetically identical bacterial cells, we ask how the phage infection dynamic reflects such heterogeneity. Here, we introduce a timelapse imaging assay for investigating the dynamics of individual infection steps by a single T7 phage on a single bacterium. This high-throughput, time-resolved assay enables us to monitor the infection progression simultaneously in multiple cells, uncovering substantial heterogeneity at each step and revealing correlations between infection dynamics and the physiological state of the infected cell. Simulations of competing phage populations with different lysis time distributions reveal that heterogeneity in infection dynamics can significantly impact phage fitness, highlighting it as a potential evolutionary driver of phage-bacteria interactions.

microbiology↗

bioRxiv2024

Differential selective regimes identify categories of transposable elements with regulatory function

Transposable elements (TEs) are powerful drivers of genome evolution, in part through their ability to rapidly rewire the host regulatory network by creating transcription factor binding sites that can potentially be turned to the hosts advantage in a process called exaptation. However, the effects on the host phenotype vary widely among different TEs. Here, we classify TEs based on their contribution to the human host phenotypes at both molecular and macroscopic scales. TE contributions to chromatin accessibility, gene expression, and the heritability of complex traits are strongly correlated to each other, confirming that the main mechanism through which TEs affect the host phenotype is through the rewiring of the regulatory network. TE sequence and evolutionary features are able to explain a large fraction of the variance in phenotypic relevance, and in particular more than 50% of the variance of their contribution to the heritability of complex traits. A conspicuous exception to this pattern is represented by TEs of the ERV1 family, whose phenotypic impact cannot be explained by our model: In particular, this family includes a set of relatively young TEs whose phenotypic relevance is much larger than would be expected based on their sequence and evolutionary parameters. These TEs are involved in fast-evolving biological processes related to the interaction of the organism with its environment. In conclusion, our results confirm quantitatively that TE insertions affect the host phenotype mostly through the rewiring of its regulatory network; identify a signature of phenotypic relevance based on sequence and conservation properties; and highlight several TEs as promising candidates for functional studies.

genetics↗

bioRxiv2023

Ancestral genetic components are consistently associated with the complex trait landscape in European biobanks

The genetic structure in Europe was mostly shaped by admixture between the Western Hunter-Gatherer, Anatolian Neolithic and Steppes Yamnaya ancestral components. Such structure is regarded as a confounder in GWAS and follow-up studies, and gold-standard methods exist to correct for it. However, it is still poorly understood to which extent these ancestral components contribute to complex trait variation in present-day Europe. In this work we harness the UK Biobank to address this question. By extensive demographic simulations and incorporating previous results obtained using the Estonian Biobank, we carefully evaluate the significance and scope of our findings. Heart rate, platelet count, monocyte percentage and many other traits show stratification similar to height and pigmentation traits, likely targets of selection and divergence across ancestral groups. The consistency of our results across biobanks indicates that these ancestry-specific genetic predispositions act as a source of variability and as potential confounders in Europe as a whole.

genomics↗

bioRxiv2023

Liquid channels within B. subtilis biofilms allow the escape of trapped clones and population rescue

Phenotypic heterogeneity is one of the hallmarks of the biofilm lifestyle, where even isogenic populations give rise to spatially organized and phenotypically distinct subpopulations. One such pattern is generated by the ability of several biofilm-forming bacteria to switch between a flagellated and a matrix producing state. Here, using Bacillus subtilis as a model system, we investigate the role of this switch during biofilm development on a solid-air interface. By comparing the matrix-flagella spatio-temporal patterns in wild-type biofilms with mixtures of flagella- and matrix-null mutants biofilms, we find that pattern formation does not require a phenotypic switch that enables individual cells to respond to the local environment, but can be explained by a completely stochastic switch coupled to a phenotype-dependent fitness landscape that selects phenotypes at the population level. Integration of experiments and physical models shows that the coexistence between flagellated and matrix-producing cells provides the population with enhanced resilience to environmental changes, by enabling cells to manipulate and harness the local morphological and transport properties within the biofilm. Our results not only reveal a new evolutionary advantage of phenotypic plasticity in biofilms, but also illustrate how the biology and ecology of these populations are intrinsically tied to their physical properties.

evolutionary biology↗

bioRxiv2021

Preventing co-infection: a viral strategy with short-term benefits and long-term drawbacks

Viral superinfection occurs when multiple viral particles subsequently infect the same host. In nature, several viral species are found to have evolved diverse mechanisms to prevent superinfection (superinfection exclusion) but how this strategic choice impacts the fate of mutations in the viral population remains unclear. Using stochastic simulations, we find that genetic drift is suppressed when superinfection occurs, thus facilitating the fixation of beneficial mutations and the removal of deleterious ones. Interestingly, we also find that the competitive (dis)advantage associated with variations in life history parameters is not necessarily captured by the viral growth rate for either infection strategy. Putting these together, we then show that a mutant with superinfection exclusion will easily overtake a superinfecting population even if the latter has a much higher growth rate. Our findings suggest that while superinfection exclusion can negatively impact the long-term adaptation of a viral population, in the short-term it is ultimately a winning strategy. Author summaryViral social behaviour has recently been receiving increasing attention in the context of ecological and evolutionary dynamics of viral populations. One fascinating and still relatively poorly understood example is superinfection or co-infection, which occur when multiple viruses infect the same host. Among bacteriophages, a wide range of mechanisms have been discovered that enable phage to prevent superinfection (superinfection exclusion) even at the cost of using precious resources for this purpose. What is the evolutionary impact of this strategic choice and why do so many phages exhibit this behaviour? Here, we conduct an extensive simulation study of a phage population to address this question. In particular, we investigate the fate of viral mutations arising in an environment with a constant supply of bacterial hosts designed to mimic a "turbidostat," as these are increasingly being used in laboratory evolution experiments. Our results show that allowing superinfection in the long-term yields a population which is more capable of adapting to changes in the environment. However, when in direct competition, mutants capable of preventing superinfection experience a very large advantage over their superinfecting counterparts, even if this ability comes at a significant cost to their growth rate. This indicates that while preventing superinfection can negatively impact the long-term prospects of a viral population, in the short-term it is ultimately a winning strategy.

evolutionary biology↗

bioRxiv2020

Virus-host interactions shape viral dispersal giving rise to distinct classes of travelling waves in spatial expansions

Reaction-diffusion waves have long been used to describe the growth and spread of populations undergoing a spatial range expansion. Such waves are generally classed as either pulled, where the dynamics are driven by the very tip of the front and stochastic fluctuations are high, or pushed, where cooperation in growth or dispersal results in a bulk-driven wave in which fluctuations are suppressed. These concepts have been well studied experimentally in populations where the cooperation leads to a density-dependent growth rate. By contrast, relatively little is known about experimental populations that exhibit density-dependent dispersal. Using bacteriophage T7 as a test organism, we present novel experimental measurements that demonstrate that the diffusion of phage T7, in a lawn of host E. coli, is hindered by steric interactions with host bacteria cells. The coupling between host density, phage dispersal and cell lysis caused by viral infection results in an effective density-dependent diffusion coefficient akin to cooperative behavior. Using a system of reaction-diffusion equations, we show that this effect can result in a transition from a pulled to pushed expansion. Moreover, we find that a second, independent density-dependent effect on phage dispersal spontaneously emerges as a result of the viral incubation period, during which phage is trapped inside the host unable to disperse. Additional stochastic agent-based simulations reveal that lysis time dramatically affects the rate of diversity loss in viral expansions. Taken together, our results indicate both that bacteriophage can be used as a controllable laboratory population to investigate the impact of density-dependent dispersal on evolution, and that the genetic diversity and adaptability of expanding viral populations could be much greater than is currently assumed.

biophysics↗

bioRxiv2019

Impact of crowding on the diversity of expanding populations

Crowding effects are key to the self-organization of densely packed cellular assemblies, such as biofilms, solid tumors, and developing tissues. When cells grow and divide they push each other apart, remodeling the structure and extent of the populations range. It has recently been shown that crowding has a strong impact on the strength of natural selection. However, the impact of crowding on neutral processes remains unclear, which controls the fate of new variants as long as they are rare. Here, we quantify the genetic diversity of expanding microbial colonies and uncover signatures of crowding in the site frequency spectrum. By combining Luria-Delbruck fluctuation tests, lineage tracing in a novel microfluidic incubator, cell-based simulations, and theoretical modeling, we find that the majority of mutations arise behind the expanding frontier, giving rise to clones that are mechanically "pushed out" of the growing region by the proliferating cells in front. These excluded-volume interactions result in a clone size distribution that solely depends on where the mutation first arose relative to the front and is characterized by a simple power-law for low-frequency clones. Our model predicts that the distribution only depends on a single parameter, the characteristic growth layer thickness, and hence allows estimation of the mutation rate in a variety of crowded cellular populations. Combined with previous studies on high-frequency mutations, our finding provides a unified picture of the genetic diversity in expanding populations over the whole frequency range and suggests a practical method to assess growth dynamics by sequencing populations across spatial scales. Significance StatementGrowing cell populations become densely packed as cells proliferate and fill space. Crowding prevents spatial mixing of individuals, significantly altering the evolutionary outcome from established results for well-mixed populations. Despite the fundamental differences between spatial and well-mixed populations, little is known about the impact of crowding on genetic diversity. Looking at microbial colonies growing on plates, we show that the allele frequency spectrum is characterized by a simple power law for low frequencies. Using cell-based simulations and microfluidic experiments, we identify the origin of this distribution in the volume-exclusion interactions within the crowded cellular environment, enabling us to extend this findings to a broad range of densely packed populations. This study highlights the importance of cellular crowding for the emergence of rare genetic variants.

biophysics↗

bioRxiv2018

Collective motion conceals fitness differences in crowded cellular populations

Many cellular populations are tightly-packed, for example microbial colonies and biofilms [39, 10, 41], or tissues and tumors in multi-cellular organisms [11, 29]. Movement of one cell inside such crowded assemblages requires movement of others, so that cell displacements are correlated over many cell diameters [28, 6, 31]. Whenever movement is important for survival or growth [15, 34, 38, 9], such correlated rearrangements could couple the evolutionary fate of different lineages. Yet, little is known about the interplay between mechanical stresses and evolution in dense cellular populations. Here, by tracking deleterious mutations at the expanding edge of yeast colonies, we show that crowding-induced collective motion prevents costly mutations from being weeded out rapidly. Joint pushing by neighboring cells generates correlated movements that suppress the differential displacements required for selection to act. Such mechanical screening of fitness differences allows the mutants to leave more descendants than expected under non-mechanical models, thereby increasing their chance for evolutionary rescue [2, 5]. Our work suggests that mechanical interactions generally influence evolutionary outcomes in crowded cellular populations, which has to be considered when modeling drug resistance or cancer evolution [1, 22, 34, 30, 36, 42].

biophysics↗