Biology subjects

Genovesio, A.

Publications and source records attributed to Genovesio, A..

At least 19 recordsLinked to original sources

bioRxiv2026

Static2Dynamic: Reconstructing videos of unobservable cellular, developmental, and disease processes

A fundamental limitation in biology is that many of its most important processes unfold as visual dynamics that cannot be directly observed. Development, tissue remodeling, and disease progression often occur deep in living organisms, over extended timescales, and at cellular resolution beyond the reach of current live imaging technologies. As a result, much of biology remains accessible only through static snapshots, while the underlying phenotypic trajectories and visual transformations remain hidden. Here, we introduce Static2Dynamic, a general framework to reconstruct unseen biological dynamics from sets of cross-sectional image data. Starting from time-unpaired static samples, Static2Dynamic first recovers a continuous pseudotime for individual images in a time-discriminative deep representation space, then learns a generative model of images conditionally to the underlying process, and finally reconstructs temporally coherent videos initialized from real samples. This makes it possible to infer past and future visual states of a static image and to simulate complete trajectories of cellular, developmental, and disease processes that were never directly recorded. We quantitatively validate Static2Dynamic on two large-scale experimental microscopy video datasets generated specifically for benchmarking, enabling direct comparison of inferred pseudotime trajectories and reconstructed videos against ground-truth biological dynamics. We further show that the framework generalizes across biological scales, organisms, and imaging modalities, including processes inaccessible to continuous live observation. More broadly, Static2Dynamic establishes the foundations of pseudotime microscopy, a new paradigm for reconstructing the visual and temporal dynamics of biological processes directly from static imaging data, thereby expanding the observable space of living systems beyond current experimental limits.

bioinformatics↗

bioRxiv2025

Large Scale Cell Painting Guided Compound Selection Reveals Activity Cliffs and Functional Relationships

Traditional structure-based pre-screen compound selection relies on the assumption that chemical similarity implies similar biological activity. This paradigm narrows the exploration of chemical space and often fails to account for functional convergence, where structurally diverse compounds act through distinct targets to produce similar phenotypic effects. As a result, compounds with therapeutic potential may be overlooked. To overcome this constraint, we introduce a training-free, transfer learning-based method for large scale compound preselection that leverages deep phenotypic profiling of human cells. Notably, this enables robust pairwise comparison of phenotypic signatures across any source of the entire JUMP-CP, the largest publicly available cell painting dataset (112,480 compounds), preserving biological signals while mitigating batch effects. Validated across 65 high-throughput assays--including in vitro and in cellulo systems--our method provides efficient pre-screen enrichment of biologically active compounds, bypassing the blind spots of structure-centric approaches. Interestingly, because it is large scale, it also allows for a comprehensive analysis of structure-phenotypic activity relationships, revealing potentially thousands of compound activity cliffs, where minimal chemical changes in structure may result in profound phenotypic shifts. We show that these cliffs capture subtle, atom-level determinants of bioactivity that cannot be accessed by structure-based models. Furthermore, we demonstrate that structurally diverse compounds targeting different genes in the same biological pathway can induce either convergent or opposite phenotypes--a phenomenon validated across 30 pathways, hundreds of genes, and thousands of compounds. Finally, to support the broader community, we propose Phenoseeker, a web-based tool enabling instant retrieval of JUMP-CP compounds with similar phenotypic profiles. Together, these findings position phenotypic profiling not merely as a complementary tool, but as a transformative and scalable framework for navigating chemical space through a biological lens. By capturing rich morphological signatures that reflect functional outcomes--regardless of structural similarity--this approach enables the discovery of bioactive compounds, novel mechanisms of action, and unexpected target-pathway relationships. Applied at the scale of the JUMP-CP dataset, phenotypic profiling emerges as a powerful strategy for prioritizing compounds, illuminating activity cliffs, and accelerating the identification of therapeutically relevant candidates across diverse biological contexts.

bioinformatics↗

bioRxiv2025

In vivo autofluorescence lifetime imaging of the Drosophila brain captures metabolic shifts associated with memory formation

Neuronal energy regulation is increasingly recognized as a critical factor underlying brain functions and their pathological alterations, yet the metabolic dynamics that accompany cognitive processes remain poorly understood. As a label-free and minimally invasive technique, fluorescence lifetime imaging (FLIM) of coenzymes NADH and NADPH (collectively referred to as NAD(P)H) offers the possibility to resolve cellular metabolic profiles with high spatial precision. However, NAD(P)H FLIMs capacity to detect subtle variations in neuronal metabolism has not been demonstrated. In this study, we applied NAD(P)H FLIM to map the metabolic profiles of Drosophila neurons in vivo across multiple scales, focusing on the primary centers for associative memory: the mushroom bodies (MBs). At a broad scale, we obtained an overview of the metabolic signatures of the main brain tissue and identified a marked difference between neuropil and cortex areas. At a finer scale, our findings revealed notable heterogeneity in the basal metabolic profiles of distinct MB neuron subtypes. Measurements performed after associative olfactory learning also uncovered a low-magnitude subtype-specific metabolic shift associated with memory formation, suggesting the utility of NAD(P)H FLIM in detecting physiology-driven changes linked to brain function. These results establish a promising framework for studying the spatial heterogeneities and the dynamics of cerebral energy metabolism in vivo.

neuroscience↗

bioRxiv2024

Dynamic Attentional Control Through Mixed Prefrontal Cortex Resources

Spatial attention can be either involuntarily drawn to salient, unexpected events (exogenous attention) or voluntarily directed (endogenous attention). Evidence suggests a link of both forms of attention to the (oculo)motor system. We investigated the role of the prefrontal cortex (PFC) in this relationship using a task that spatially dissociated attention from motor planning in two monkeys. PFC units flexibly encoded either the attended location or motor target, with some showing overlapping coding. Endogenous attention promotes an early engagement of these shared resources, producing two key effects: (1) it prevents interference between motor and attention systems, and (2) it regulates the extent of the exogenous shifts for attentional capture, with stronger shifts occurring when endogenous attention is weak. Overall, we show that there are separate attention and motor systems, each of which can flexibly draw on some "overlapping" resources based on environmental and internal demands.

neuroscience↗

bioRxiv2024

Out of the single-neuron straitjacket: neurons within assemblies change selectivity and their reconfiguration underlies dynamic coding

We investigated cell assemblies in the frontal cortex of macaques during two discrimination tasks. Focusing on the period of goal-action transformation, we extracted spikes fired during assembly activation from the full neural activity and showed that the contribution of a neuron to assembly coding, when it coordinates with other assembly neurons, differs from its coding in isolation. Neurons with their flexible participation to multiple assemblies contributed to the encoding of new information not encoded by the neurons alone. Even non-discriminative neurons acquired selectivity as part of the collective activity of the assemblies. Thus, neurons in their assemblies process distinct information for various purposes as a chess simul master, playing on multiple chessboards. The reconfiguration of the participation of the neurons into different assemblies in the goal-action transformation process translated into a dynamic form of coding, whereas minimal reconfiguration was associated with the static goal coding of the memory period.

neuroscience↗

bioRxiv2024

History bias and its perturbation of the stimulus representation in the macaque prefrontal cortex.

Multiple history biases affect our representation of magnitudes, such as time, distance, and size. It is not clear whether the previous stimuli interfere with the discrimination process from the moment of stimulus presentation, during working memory retention, or even later during the decision-making phase. We used a spatial discrimination task involving two stimuli of different magnitudes, presented sequentially at various distances from the center. The monkeys task was to select the farthest of them. We showed that the previous stimulus magnitude generated a contraction bias effect, but only when its stimulus features differed from those of the current stimulus. In this case, at the neural level we also observed that the decoding of the stimulus magnitude achieved the highest accuracy when it matched the magnitude of the preceding stimulus for which the decoder was trained. This indicates that past stimuli can affect magnitude processing already during the stimulus presentation, even before the decision process. Interestingly, this effect manifested when the trace of the previous stimulus magnitude reactivated in the second part of the stimulus presentation after an "activity-silent" period.

neuroscience↗

bioRxiv2024

From solo to collaborative: the global increase in neuroscience authors over two decades

The increase in the number of authors per article is a well-documented phenomenon across various academic disciplines. While prior studies have examined this trend in specific fields and countries, they in most cases did not compare the increase in the number of authors between countries. While it has previously shown that the number of authors in neuroscience publications has risen in the G10 countries, no study has yet addressed whether it reflects a global trend in the field. To address this gap, we quantified the global trend in the number of authors in neuroscience publications from 2001 to 2022. Our findings reveal a consistent increase in authorship across nearly all the countries examined. Italy ranks highest in terms of average authorship per article, while Ukraine ranks the lowest. On the other hand, China shows the largest increase in authorship over the years, followed by Norway and Egypt. South Korea is the only country showing a slight decreasing trend rather than growth. These results contribute to a better understanding of authorship patterns in neuroscience, and can stimulate further investigations on the reasons behind such an increase in terms of socio-economic factors, the need for collaborative efforts in some fields, or, on the negative side, the effect of utilitarian reasons to meet career evaluation criteria.

neuroscience↗

bioRxiv2024

The Increasing Authorship trend in Neuroscience: A scientometric analysis across 11 countries

Previous studies have demonstrated an increasing trend of the number of authors across various fields over the years. This trend has been attributed to the necessity for larger collaborations and, at times, to ethical issues regarding authorship attribution. Our study focuses on the evolution of authorship trends in the field of Neuroscience. We conducted our analysis based on a dataset containing 576,647 neuroscience publications produced from 2000 to 2022, focusing on the publications within the Group of ten (G10) countries. Using a matrix-based methodology, we extracted and analyzed the average number of authors per country. Our findings reveal a consistent rise in authorship across all G10 countries over the past two decades. Italy emerged with the highest average number of authors, while the Netherlands stood out for experiencing the most significant increase, particularly in the last decade. The countries with the lowest number of authors per publication were the USA, UK, and Canada.

neuroscience↗

bioRxiv2022

Neural representational geometry correlates with behavioral differences between monkeys

Animals likely use a variety of strategies to solve laboratory tasks. Traditionally, combined analysis of behavioral and neural recording data across subjects employing different strategies may obscure important signals and give confusing results. Hence, it is essential to develop techniques that can infer strategy at the single-subject level. We analyzed an experiment in which two monkeys performed a visually cued rule-based task. The analysis of their performance shows no indication that they used a different strategy. However, when we examined the geometry of stimulus representations in the state space of the neural activities recorded in dorsolateral prefrontal cortex, we found striking differences between the two monkeys. Our purely neural results induced us to reanalyze the behavior. The new analysis showed that the differences in representational geometry correlate with differences in the reaction times, revealing behavioral differences we were unaware of. All these analyses indicate that the monkeys are using different strategies. Finally, using recurrent neural network models trained to perform the same task, we show that these strategies correlate with the amount of training, suggesting a possible explanation for the observed neural and behavioral differences.

neuroscience↗

bioRxiv2022

Revealing invisible cell phenotypes with conditional generative modeling

Biological sciences, drug discovery and medicine rely heavily on cell phenotype perturbation and observation. Aside from dramatic events such as cell division or cell death, most cell phenotypic changes that keep cells alive are subtle and thus hidden from us by natural cell variability: two cells in the same condition already look different. While we show that deep learning models can leverage invisible features from microscopy images, to discriminate between close conditions, these features can yet hardly be observed and therefore interpreted. In this work, we show that conditional generative models can be used to transform an image of cells from any one condition to another, thus canceling cell variability. We visually and quantitatively validate that the principle of synthetic cell perturbation works on discernible cases such as high concentration drug treatments, nuclear translocation and golgi apparatus assays. We then illustrate its effectiveness in displaying otherwise invisible cell phenotypes triggered by blood cells under parasite infection, the presence of a disease-causing pathological mutation in differentiated neurons derived from iPSCs or low concentration drug treatments. The proposed approach, easy to use and robust, opens the door to the accessible discovery of biological and disease biomarkers.

bioinformatics↗

bioRxiv2022

Evolution is not uniform along protein sequences

Amino acids evolve at different speeds within protein sequences, because their functional and structural roles are different. However, the position of an amino-acid within the sequence is not known to influence this evolutionary speed. Here we discovered that amino-acid evolve almost twice faster at protein termini than in their centre, hinting at a strong topological bias along the sequence length. We further show that the distribution of functional domains and of solvent-accessible residues in proteins readily explain how functional constrains are weaker at their termini, leading to the observed excess of amino-acid substitutions. Finally, we show that methods inferring sites under positive selection are strongly biased towards protein termini, suggesting that they may confound positive selection with weak negative selection. These results suggest that accounting for positional information should improve evolutionary models.

evolutionary biology↗

bioRxiv2021

Different contribution of the monkey prefrontal and premotor dorsal cortex in decision-making supported by inferential reasoning

Several studies have reported similar neural modulations between brain areas of the frontal cortex, such as the dorsolateral prefrontal (DLPFC) and the premotor dorsal (PMd) cortex, in tasks requiring encoding of the abstract rules for selecting the proper action. Here we compared the neuronal modulation of the DLPFC and PMd of monkeys trained to choose the higher rank from a pair of abstract images (target item), selected from an arbitrarily rank-ordered set (A>B>C>D>E>F) in the context of a transitive inference task. Once acquired by trial-and-error, the ordinal relationship between pairs of adjacent images (i.e., A>B; B>C; C>D; D>E; E>F), monkeys were tested in indicating the ordinal relation between items of the list not paired during learning. During these decisions, we observed that the choice accuracy increased and the reaction time decreased as the rank difference between the compared items enhanced. This result is in line with the hypothesis that after learning, the monkeys built an abstract mental representation of the ranked items, where rank comparisons correspond to the items position comparison on this representation. In both brain areas, we observed higher neuronal activity when the target item appeared in a specific location on the screen with respect to the opposite position and that this difference was particularly enhanced at lower degrees of difficulty. By comparing the time evolution of the activity of the two areas, we observed that the neural encoding of target item spatial position occurred earlier in the DLPFC than in the PMd.

animal behavior and cognition↗

bioRxiv2021

An executive center for the intake of liquids

It has long been known that orofacial movements for feeding can be triggered, coordinated, and often rhythmically organized at the level of the brainstem, without input from higher centers. We uncover two nuclei that can organize the movements for ingesting fluids in mammals. These neuronal groups, defined by unique transcriptional codes and developmental origins, IRtPhox2b and Peri5Atoh1, are located, respectively, in the intermediate reticular formation of the medulla and around the motor nucleus of the trigeminal nerve. They are premotor to all jaw-opening and tongue muscles. Stimulation of either, in awake animals, opens the jaw, while IRtPhox2b alone also protracts the tongue. Moreover, stationary stimulation of IRtPhox2b entrains a rhythmic alternation of tongue protraction and retraction, synchronized with jaw opening and closing, that mimics lapping. Finally, fiber photometric recordings show that IRtPhox2b is active during volitional lapping. Our study identifies one of the long hypothesized subcortical nuclei underpinning a stereotyped feeding behavior.

neuroscience↗

bioRxiv2021

Evolutionary analysis of DNA methyltransferases in microeukaryotes: Insights from the model diatom Phaeodactylum tricornutum

Cytosine methylation is an important epigenetic mark involved in the transcriptional control of transposable elements in mammals, plants and fungi. The Stramenopiles-Alveolate-Rhizaria (SAR) lineages are a major group of ecologically important marine microeukaryotes that include the main phytoplankton groups diatoms and dinoflagellates. However, little is known about their DNA methyltransferase diversity. Here, we performed an in-silico analysis of DNA methyltransferases found in marine microeukaryotes and showed that they encode divergent DNMT3, DNMT4, DNMT5 and DNMT6 enzymes. Furthermore, we found three classes of enzymes within the DNMT5 family. Using a CRISPR/Cas9 strategy we demonstrated that the loss of the DNMT5a gene correlates with a global depletion of DNA methylation and overexpression of young transposable elements in the model diatom Phaeodactylum tricornutum. The study provides a pioneering view of the structure and function of a DNMT family in the SAR supergroup using an attractive model species.

genomics↗

bioRxiv2021

Intrinsic Timescales Across the Basal Ganglia

Recent studies have shown that neuronal stability over time can be estimated by the structure of the spike-count autocorrelation of neuronal populations. This estimation, called the intrinsic timescale, has been computed for several cortical areas and can be used to propose a cortical hierarchy reflecting a scale of temporal receptive windows between areas. In this study, we performed an autocorrelation analysis on neuronal populations of three basal ganglia (BG) nuclei, including the striatum and the subthalamic nucleus (STN), the input structures of the BG, and the external globus pallidus (GPe). The analysis was performed during the baseline period of a motivational visuomotor task in which monkeys had to apply different amounts of force to receive a different amount of reward. We found that the striatum and the STN have longer intrinsic timescales than the GPe. Moreover, our results allow for the placement of these subcortical structures within the already-defined scale of cortical temporal receptive windows. Estimates of intrinsic timescales are important in adding further constraints in the development of computational models of the complex dynamics among these nuclei and throughout cortico-BG-thalamo-cortical loops.

neuroscience↗

bioRxiv2021

Slower prefrontal metastable dynamics during deliberation predicts error trials in a distance discrimination task

AO_SCPLOWBSTRACTC_SCPLOWPrevious studies have established the involvement of prefrontal cortex (PFC) neurons in decision processes in many task contexts. Single neurons and populations of neurons have been found to represent stimuli, actions, and internal deliberations. However, it is much less clear which underlying computations are affected during errors. Neural activity during errors can help to disambiguate confounds and clarify which computations are essential during a specific task. Here, we used a hidden Markov model (HMM) to perform a trial-by-trial analysis of ensembles of simultaneously recorded neurons from the dorsolateral prefrontal (PFdl) cortex of two rhesus monkeys performing a distance discrimination task. The HMM segments the neural activity into sequences of metastable states, allowing to link neural ensemble dynamics with task and behavioral features in the absence of external triggers. We report a precise relationship between the modulation of the metastable dynamics and task features. Specifically, we found that errors were made more often when the metastable dynamics slowed down, while trial difficulty influenced the latency of state transitions at a pivotal point during the trial. Both these phenomena occurred during the decision interval and not following the action, with errors occurring in both easy and difficult trials. Thus, modulations of metastable dynamics reflected a state of internal deliberation rather than actions taken or, in the case of error trials, objective trial difficulty. Our results show that temporal modulations of PFdl activity are key determinants of internal deliberations, providing further support for the emerging role of metastable cortical dynamics in mediating complex cognitive functions and behavior.

neuroscience↗

bioRxiv2019

H3K27me3 natural variation selectively marks genes predicted to be important for differentiation in unicellular algae

O_LIIn multicellular organisms, Polycomb Repressive Complex2 (PRC2) is known to deposit H3K27me3 to establish and maintain gene silencing, critical for developmentally regulated processes. PRC2 complex is absent in both widely studied model yeasts which initially suggested that PRC2 arose with the emergence of multicellularity. However, its discovery in several unicellular species including microalgae questions its role in unicellular eukaryotes. C_LIO_LIHere, we use Phaeodactylum tricornutum enhancer of zeste E(z) knockouts and show that P. tricornutum E(z) is responsible for di and tri-methylation of lysine 27 of histone H3. C_LIO_LIH3K27me3 depletion abolishes cell morphology in P. tricornutum providing evidence for its role in cell differentiation. Genome wide profiling of H3K27me3 in fusiform and triradiate cells further revealed genes that may specify cell identity. C_LIO_LIThese results suggest a role for PRC2 and its associated mark in cell differentiation in unicellular species and highlight their ancestral function in a broader evolutionary context than is currently appreciated. C_LI

cell biology↗

bioRxiv2019

Coordination of transcriptional and translational regulations in human cells infected by Listeria monocytogenes

The invasion of mammalian cells by intracellular bacterial pathogens reshuffles their gene expression and functions; however, we lack dynamic insight into the distinct control levels that shape the host response. Here, we have addressed the respective contribution of transcriptional and translational regulations during a timecourse of infection of human intestinal epithelial cells by an epidemic strain of Listeria monocytogenes, using transcriptome analysis paralleled with ribosome profiling. Upregulations were dominated by early transcriptional activation of pro-inflammatory genes, whereas translation inhibition appeared as the major driver of downregulations. Instead of a widespread but transient shutoff, translation inhibition affected specifically and durably transcripts encoding components of the translation machinery harbouring a 5-terminal oligopyrimidine motif. Pre-silencing the most repressed target gene (PABPC1) slowed down the intracellular multiplication of Listeria monocytogenes, suggesting that the infected host cell can benefit from the repression of genes involved in protein synthesis and thereby better control infection.

molecular biology↗