Biophysical determinants of virus-cell interaction at the single particle level.

Clathrin-mediated endocytosis (CME) is one of the major endocytic pathways among eukaryotic organisms. Importantly, this pathway is also hijacked by many pathogens, such as viruses, in order to enter and infect cells. Since the first identification of Clathrin-coated endocytic vesicles, in 1964, CME has been thoroughly characterized and more than 50 proteins have been described to be part of this pathway. Nevertheless, which protein plays a main regulatory function during initiation and which factors are involved in inducing CME activation upon virus binding and internalization is still a matter of debate. Studying the early determinants of virus-cell early interaction and CME recruitment represents an extremely challenging topic due to the fact that such events take place in an extremely narrow time window and are spatially unpredictable. In this work, I describe a novel method to covalently immobilize virus particles onto glass surfaces in order to study early host-pathogens interactions. To specifically address the role of the mechanical vs receptor-mediated properties of viruses in inducing CME activation, latex beads of several sizes were immobilized using the same established approach. By combining surface chemistry, click chemistry and several microscopy techniques (fluorescence live microscopy, super resolution microscopy and electron microscopy) it was possible to unveil new details of early virus–cell interaction. In particular, I could confirm that CME recruitment is dependent on the size of the cargo. Specifically, sizes between 80 to 300 nm in diameter, can favor CME activation independently from receptor binding (mechanical induction). Surprisingly, it was discovered that the maturation process that leads to the formation of Clathrin-coated vesicles (CCVs) is independent from cargo internalization and that the size of the CCVs is imprinted on the Clathrin coat at the early cargo-cell interaction. These results could not be unveiled with canonical cell biology techniques. Interestingly, recruitment of CME can be favored on nanoparticles whose size is below the critical diameter to support mechanical induction (< 80 nm), by artificially inducing receptor engagement/clustering. Taken together these results demonstrate the presence of a fine-tuning between mechanical induction and receptor activation during early virus-cell interaction; this balance plays a major role in virus infection. The established method can be applied in future studies in the field of virology and endocytosis aiming at understanding how different pathogens favor their internalization using certain pathways, which proteins play a major role in endocytosis initiation and which early factors (mechanical VS receptor-mediated) play a role in activating one pathway over the other

Task-Related modulations of BOLD low-frequency fluctuations within the default mode Network

Spontaneous low-frequency Blood-Oxygenation Level-Dependent (BOLD) signals acquired during resting state are characterized by spatial patterns of synchronous fluctuations, ultimately leading to the identification of robust brain networks. The resting-state brain networks, including the Default Mode Network (DMN), are demonstrated to persist during sustained task execution, but the exact features of task-related changes of network properties are still not well characterized. In this work we sought to examine in a group of 20 healthy volunteers (age 33 ± 6 years, 8 F/12 M) the relationship between changes of spectral and spatiotemporal features of one prominent resting-state network, namely the DMN, during the continuous execution of a working memory n-back task. We found that task execution impacted on both functional connectivity and amplitude of BOLD fluctuations within large parts of the DMN, but these changes correlated between each other only in a small area of the posterior cingulate. We conclude that combined analysis of multiple parameters related to connectivity, and their changes during the transition from resting state to continuous task execution, can contribute to a better understanding of how brain networks rearrange themselves in response to a task

emerging and potentially emerging viruses in water environments

Among microorganisms, viruses are best fit to become emerging pathogens since they are able to adapt not only by mutation but also through recombination and reassortment and can thus become able to infect new hosts and to adjust to new environments. Enteric viruses are among the commonest and most hazardous waterborne pathogens, causing both sporadic and outbreak-related illness. The main health effect associated with enteric viruses is gastrointestinal illness, but they can also cause respiratory symptoms, conjunctivitis, hepatitis, central nervous system infections, and chronic diseases. Non-enteric viruses, such as respiratory and epitheliotrophic viruses are not considered waterborne, as they are not readily transmitted to water sources from infected individuals. The present review will focus on viral pathogens shown to be transmitted through water. It will also provide an overview of viruses that had not been a concern for waterborne transmission in the past, but that may represent potentially emerging waterborne pathogens due to their occurrence and persistence in water environments

Scale-invariant rearrangement of resting state networks in the human brain under sustained stimulation

Brain activity at rest is characterized by widely distributed and spatially specific patterns of synchronized low-frequency blood-oxygenation level-dependent (BOLD) fluctuations, which correspond to physiologically relevant brain networks. This network behaviour is known to persist also during task execution, yet the details underlying task-associated modulations of within- and between-network connectivity are largely unknown. In this study we exploited a multi-parametric and multi-scale approach to investigate how low-frequency fluctuations adapt to a sustained n-back working memory task. We found that the transition from the resting state to the task state involves a behaviourally relevant and scale-invariant modulation of synchronization patterns within both task-positive and default mode networks. Specifically, decreases of connectivity within networks are accompanied by increases of connectivity between networks. In spite of large and widespread changes of connectivity strength, the overall topology of brain networks is remarkably preserved. We show that these findings are strongly influenced by connectivity at rest, suggesting that the absolute change of connectivity (i.e., disregarding the baseline) may not be the most suitable metric to study dynamic modulations of functional connectivity. Our results indicate that a task can evoke scale-invariant, distributed changes of BOLD fluctuations, further confirming that low frequency BOLD oscillations show a specialized response and are tightly bound to task-evoked activation

Brain Network Modularity During a Sustained Working-Memory Task

Spontaneous oscillations of the blood oxygenation level-dependent (BOLD) signal are spatially synchronized within specific brain networks and are thought to reflect synchronized brain activity. Networks are modulated by the performance of a task, even if the exact features and degree of such modulations are still elusive. The presence of networks showing anticorrelated fluctuations lend initially to suppose that a competitive relationship between the default mode network (DMN) and task positive networks (TPNs) supports the efficiency of brain processing. However, more recent results indicate that cooperative and competitive dynamics between networks coexist during task performance. In this study, we used graph analysis to assess the functional relevance of the topological reorganization of brain networks ensuing the execution of a steady state working-memory (WM) task. Our results indicate that the performance of an auditory WM task is associated with a switching between different topological configurations of several regions of specific networks, including frontoparietal, ventral attention, and dorsal attention areas, suggesting segregation of ventral attention regions in the presence of increased overall integration. However, the correct execution of the task requires integration between components belonging to all the involved networks