Continuos Flow Single Cell Separation into Open Microwell Arrays

A novel design based on electric field-free open microwell arrays for the automated continuous-flow sorting of single or small clusters of cells is presented. The main feature of the proposed device is the parallel analysis of cell-cell and cell-particle interactions in each microwell of the array. High throughput sample recovery with a fast and separate transfer from the microsites to standard microtiter plates is also possible thanks to the flexible printed circuit board technology which permits to produce cost effective large area arrays featuring geometries compatible with laboratory equipment. The particle isolation is performed via negative dielectrophoretic forces which convey the particles’ into the microwells. Particles such as cells and beads flow in electrically active microchannels on whose substrate the electrodes are patterned. The introduction of particles within the microwells is automatically performed by generating the required feedback signal by a microscope-based optical counting and detection routine. In order to isolate a controlled number of particles we created two particular configurations of the electric field within the structure. The first one permits their isolation whereas the second one creates a net force which repels the particles from the microwell entrance. To increase the parallelism at which the cell-isolation function is implemented, a new technique based on coplanar electrodes to detect particle presence was implemented. A lock-in amplifying scheme was used to monitor the impedance of the channel perturbed by flowing particles in high-conductivity suspension mediums. The impedance measurement module was also combined with the dielectrophoretic focusing stage situated upstream of the measurement stage, to limit the measured signal amplitude dispersion due to the particles position variation within the microchannel. In conclusion, the designed system complies with the initial specifications making it suitable for cellomics and biotechnology applications.

Phenotypic and molecular investigation of circulating tumor cells (CTCs) isolated from breast cancer patients at single cell resolution

Despite the paramount advances in cancer research, breast cancer (BC) still ranks one of the leading causes of cancer-related death worldwide. Thanks to the screening campaign started in developed countries, BC is often diagnosed at early stages (non-metastatic BC, nmBC), but disease relapse occurrence even after decades and at distant sites is not an uncommon phenomenon. Conversely, metastatic BC (mBC) is considered an incurable disease. The major perpetrators of tumor spread to secondary organs are circulating tumor cells (CTCs), a rare population of cells detectable in the peripheral blood of oncologic patients. In this study, CTCs from patients diagnosed with luminal nmBC and mBC (hormone receptor positive, Human Epidermal Growth Factor Receptor 2 (HER2) negative) were characterized at both phenotypic and molecular levels. To better understand the molecular mechanisms underlying their biology and their metastatic potential, next-generation sequencing (NGS) analyses were performed at single-cell resolution to assess copy number aberrations (CNAs), single nucleotide variants (SNVs) and gene expression profiling. The findings of this study arise hints in CTC detection, and pave the way to new application in CTC research.

Elf magnetic field influence on ION Channels studied by Patch Clamp Technique: exposure set up and "Whole Cell" measurements on Potassium currents

The aim of this thesis was to study the effects of extremely low frequency (ELF) electromagnetic magnetic fields on potassium currents in neural cell lines ( Neuroblastoma SK-N-BE ), using the whole-cell Patch Clamp technique. Such technique is a sophisticated tool capable to investigate the electrophysiological activity at a single cell, and even at single channel level. The total potassium ion currents through the cell membrane was measured while exposing the cells to a combination of static (DC) and alternate (AC) magnetic fields according to the prediction of the so-called ‘ Ion Resonance Hypothesis ’. For this purpose we have designed and fabricated a magnetic field exposure system reaching a good compromise between magnetic field homogeneity and accessibility to the biological sample under the microscope. The magnetic field exposure system consists of three large orthogonal pairs of square coils surrounding the patch clamp set up and connected to the signal generation unit, able to generate different combinations of static and/or alternate magnetic fields. Such system was characterized in term of field distribution and uniformity through computation and direct field measurements. No statistically significant changes in the potassium ion currents through cell membrane were reveled when the cells were exposed to AC/DC magnetic field combination according to the afore mentioned ‘Ion Resonance Hypothesis’.

Genetic Manipulation, Gene Silencing and Biomarker Development in Multiple Experimental Models.

The thesis is set in three different parts, according to the relative experimental models. First, the domestic pig (Sus scrofa) is part of the study on reproductive biotechnologies: the transgenesis technique of Sperm Mediated Gene Transfer is widely studied starting from the quality of the semen, through the study of multiple uptakes of exogenous DNA and lastly used in the production of multi-transgenic blastocysts. Finally we managed to couple the transgenesis pipeline with sperm sorting and therefore produced transgenic embryos of predetermined sex. In the second part of the thesis the attention is on the fruit fly (Drosophila melanogaster) and on its derived cell line: the S2 cells. The in vitro and in vivo models are used to develop and validate an efficient way to knock down the myc gene. First an efficient in vitro protocol is described, than we demonstrate how the decrease in myc transcript remarkably affects the ribosome biogenesis through the study of Polysome gradients, rRNA content and qPCR. In vivo we identified two optimal drivers for the conditional silencing of myc, once the flies are fed with RU486: the first one is throughout the whole body (Tubulin), while the second is a head fat body driver (S32). With these results we present a very efficient model to study the role of myc in multiple aspects of translation. In the third and last part, the focus is on human derived lung fibroblasts (hLF-1), mouse tail fibroblasts and mouse tissues. We developed an efficient assay to quantify the total protein content of the nucleus on a single cell level via fluorescence. We coupled the protocol with classical immunofluorescence so to have at the same time general and particular information, demonstrating that during senescence nuclear proteins increase by 1.8 fold either in human cells, mouse cells and mouse tissues.

Electrochemical imaging of living cell metabolism: investigation on Warburg effect in cancer

Cancer is one of the principal causes of death in the world; almost 8.2 million of deaths were counted in 2012. Emerging evidences indicate that most of the tumors have an increased glycolytic rate and a detriment of oxidative phosphorylation to support abnormal cell proliferation; this phenomenon is known as aerobic glycolysis or Warburg effect. This switching toward glycolysis implies that cancer tissues metabolize approximately tenfold more glucose to lactate in a given time and the amount of lactate released from cancer tissues is much greater than from normal ones. In view of these fundamental discoveries alterations of the cellular metabolism should be considered a crucial hallmark of cancer. Therefore, the investigation of the metabolic differences between normal and transformed cells is important in cancer research and it might find clinical applications. The aim of the project was to investigate the cellular metabolic alterations at single cell level, by monitoring glucose and lactate, in order to provide a better insight in cancer research. For this purpose, electrochemical techniques have been applied. Enzyme-based electrode biosensors for lactate and glucose were –ad hoc- optimized within the project and used as probes for Scanning Electrochemical Microscopy (SECM). The UME biosensor manufacturing and optimization represented a consistent part of the work and a full description of the sensor preparation protocols and of the characterization methods employed is reported. This set-up (SECM used with microbiosensor probes) enabled the non-invasive study of cellular metabolism at single cell level. The knowledge of cancer cell metabolism is required to design more efficient treatment strategies.

Computational Modelling of Cardiac Electrophysiology: from Cell to Bedside

Heart diseases are the leading cause of death worldwide, both for men and women. However, the ionic mechanisms underlying many cardiac arrhythmias and genetic disorders are not completely understood, thus leading to a limited efficacy of the current available therapies and leaving many open questions for cardiac electrophysiologists. On the other hand, experimental data availability is still a great issue in this field: most of the experiments are performed in vitro and/or using animal models (e.g. rabbit, dog and mouse), even when the final aim is to better understand the electrical behaviour of in vivo human heart either in physiological or pathological conditions. Computational modelling constitutes a primary tool in cardiac electrophysiology: in silico simulations, based on the available experimental data, may help to understand the electrical properties of the heart and the ionic mechanisms underlying a specific phenomenon. Once validated, mathematical models can be used for making predictions and testing hypotheses, thus suggesting potential therapeutic targets. This PhD thesis aims to apply computational cardiac modelling of human single cell action potential (AP) to three clinical scenarios, in order to gain new insights into the ionic mechanisms involved in the electrophysiological changes observed in vitro and/or in vivo. The first context is blood electrolyte variations, which may occur in patients due to different pathologies and/or therapies. In particular, we focused on extracellular Ca2+ and its effect on the AP duration (APD). The second context is haemodialysis (HD) therapy: in addition to blood electrolyte variations, patients undergo a lot of other different changes during HD, e.g. heart rate, cell volume, pH, and sympatho-vagal balance. The third context is human hypertrophic cardiomyopathy (HCM), a genetic disorder characterised by an increased arrhythmic risk, and still lacking a specific pharmacological treatment.

Interrogation of human monoclonal antibodies induced by 4C-MenB to identify protective antigens contained in the OMV component

Neisseria meningitidis is a gram negative human obligated pathogen, mostly found as a commensal in the oropharyngeal mucosa of healthy individuals. It can invade this epithelium determining rare but devastating and fast progressing outcomes, such as meningococcal meningitidis and septicemia, leading to death (about 135000 per year worldwide). Conjugated vaccines for serogroups A, C, W135, X and Y were developed, while for N. meningitidis serogroup B (MenB) the vaccines were based on Outern Membrane Vesicles (OMV). One of them is the 4C-MenB (Bexsero). The antigens included in this vaccine’s formulation are, in addition to the OMV from New Zeland epidemic strain 98/254, three recombinant proteins: NadA, NHBA and fHbp. While the role of these recombinant components was deeply characterized, the vesicular contribution in 4C-MenB elicited protection is mediated mainly by porin A and other unidentified antigens. To unravel the relative contribution of these different antigens in eliciting protective antibody responses, we isolated human monoclonal antibodies (mAbs) from single-cell sorted plasmablasts of 3 adult vaccinees peripheral blood. mAbs have been screened for binding to 4C-MenB components by Luminex bead-based assay. OMV-specific mAbs were purified and tested for functionality by serum bactericidal assay (SBA) on 18 different MenB strains and characterized in a protein microarray containing a panel of prioritized meningococcal proteins. The bactericidal mAbs identified to recognize the outer membrane proteins PorA and PorB, stating the importance of PorB in cross-strain protection. In addition, RmpM, BamE, Hyp1065 and ComL were found as immunogenic components of the 4C-MenB vaccine.

Regulation of SRC-3 localization and dynamics by phosphorylation during ERα-dependent transcriptional activation

Transcription is controlled by promoter-selective transcriptional factors (TFs), which bind to cis-regulatory enhancers elements, termed hormone response elements (HREs), in a specific subset of genes. Regulation by these factors involves either the recruitment of coactivators or corepressors and direct interaction with the basal transcriptional machinery (1). Hormone-activated nuclear receptors (NRs) are well characterized transcriptional factors (2) that bind to the promoters of their target genes and recruit primary and secondary coactivator proteins which possess many enzymatic activities required for gene expression (1,3,4). In the present study, using single-cell high-resolution fluorescent microscopy and high throughput microscopy (HTM) coupled to computational imaging analysis, we investigated transcriptional regulation controlled by the estrogen receptor alpha (ERalpha), in terms of large scale chromatin remodeling and interaction with the associated coactivator SRC-3 (Steroid Receptor Coactivator-3), a member of p160 family (28) primary coactivators. ERalpha is a steroid-dependent transcriptional factor (16) that belongs to the NRs superfamily (2,3) and, in response to the hormone 17-ß estradiol (E2), regulates transcription of distinct target genes involved in development, puberty, and homeostasis (8,16). ERalpha spends most of its lifetime in the nucleus and undergoes a rapid (within minutes) intranuclear redistribution following the addition of either agonist or antagonist (17,18,19). We designed a HeLa cell line (PRL-HeLa), engineered with a chromosomeintegrated reporter gene array (PRL-array) containing multicopy hormone response-binding elements for ERalpha that are derived from the physiological enhancer/promoter region of the prolactin gene. Following GFP-ER transfection of PRL-HeLa cells, we were able to observe in situ ligand dependent (i) recruitment to the array of the receptor and associated coregulators, (ii) chromatin remodeling, and (iii) direct transcriptional readout of the reporter gene. Addition of E2 causes a visible opening (decondensation) of the PRL-array, colocalization of RNA Polymerase II, and transcriptional readout of the reporter gene, detected by mRNA FISH. On the contrary, when cells were treated with an ERalpha antagonist (Tamoxifen or ICI), a dramatic condensation of the PRL-array was observed, displacement of RNA Polymerase II, and complete decreasing in the transcriptional FISH signal. All p160 family coactivators (28) colocalize with ERalpha at the PRL-array. Steroid Receptor Coactivator-3 (SRC-3/AIB1/ACTR/pCIP/RAC3/TRAM1) is a p160 family member and a known oncogenic protein (4,34). SRC-3 is regulated by a variety of posttranslational modifications, including methylation, phosphorylation, acetylation, ubiquitination and sumoylation (4,35). These events have been shown to be important for its interaction with other coactivator proteins and NRs and for its oncogenic potential (37,39). A number of extracellular signaling molecules, like steroid hormones, growth factors and cytokines, induce SRC-3 phosphorylation (40). These actions are mediated by a wide range of kinases, including extracellular-regulated kinase 1 and 2 (ERK1-2), c-Jun N-terminal kinase, p38 MAPK, and IkB kinases (IKKs) (41,42,43). Here, we report SRC-3 to be a nucleocytoplasmic shuttling protein, whose cellular localization is regulated by phosphorylation and interaction with ERalpha. Using a combination of high throughput and fluorescence microscopy, we show that both chemical inhibition (with U0126) and siRNA downregulation of the MAP/ERK1/2 kinase (MEK1/2) pathway induce a cytoplasmic shift in SRC-3 localization, whereas stimulation by EGF signaling enhances its nuclear localization by inducing phosphorylation at T24, S857, and S860, known partecipants in the regulation of SRC-3 activity (39). Accordingly, the cytoplasmic localization of a non-phosphorylatable SRC-3 mutant further supports these results. In the presence of ERalpha, U0126 also dramatically reduces: hormone-dependent colocalization of ERalpha and SRC-3 in the nucleus; formation of ER-SRC-3 coimmunoprecipitation complex in cell lysates; localization of SRC-3 at the ER-targeted prolactin promoter array (PRL-array) and transcriptional activity. Finally, we show that SRC-3 can also function as a cotransporter, facilitating the nuclear-cytoplasmic shuttling of estrogen receptor. While a wealth of studies have revealed the molecular functions of NRs and coregulators, there is a paucity of data on how these functions are spatiotemporally organized in the cellular context. Technically and conceptually, our findings have a new impact upon evaluating gene transcriptional control and mechanisms of action of gene regulators.

Computational Modeling of Cardiac Excitation-Contraction Coupling in Physiological and Pathological Conditions

The cardiomyocyte is a complex biological system where many mechanisms interact non-linearly to regulate the coupling between electrical excitation and mechanical contraction. For this reason, the development of mathematical models is fundamental in the field of cardiac electrophysiology, where the use of computational tools has become complementary to the classical experimentation. My doctoral research has been focusing on the development of such models for investigating the regulation of ventricular excitation-contraction coupling at the single cell level. In particular, the following researches are presented in this thesis: 1) Study of the unexpected deleterious effect of a Na channel blocker on a long QT syndrome type 3 patient. Experimental results were used to tune a Na current model that recapitulates the effect of the mutation and the treatment, in order to investigate how these influence the human action potential. Our research suggested that the analysis of the clinical phenotype is not sufficient for recommending drugs to patients carrying mutations with undefined electrophysiological properties. 2) Development of a model of L-type Ca channel inactivation in rabbit myocytes to faithfully reproduce the relative roles of voltage- and Ca-dependent inactivation. The model was applied to the analysis of Ca current inactivation kinetics during normal and abnormal repolarization, and predicts arrhythmogenic activity when inhibiting Ca-dependent inactivation, which is the predominant mechanism in physiological conditions. 3) Analysis of the arrhythmogenic consequences of the crosstalk between β-adrenergic and Ca-calmodulin dependent protein kinase signaling pathways. The descriptions of the two regulatory mechanisms, both enhanced in heart failure, were integrated into a novel murine action potential model to investigate how they concur to the development of cardiac arrhythmias. These studies show how mathematical modeling is suitable to provide new insights into the mechanisms underlying cardiac excitation-contraction coupling and arrhythmogenesis.

The role of medial parieto occipital cortex in visuospatial attention and reach planning: electrophysiological studies in human and non-human primates

We usually perform actions in a dynamic environment and changes in the location of a target for an upcoming action require both covert shifts of attention and motor planning update. In this study we tested whether, similarly to oculomotor areas that provide signals for overt and covert attention shifts, covert attention shifts modulate activity in cortical area V6A, which provides a bridge between visual signals and arm-motor control. We performed single cell recordings in monkeys trained to fixate straight-ahead while shifting attention outward to a peripheral cue and inward again to the fixation point. We found that neurons in V6A are influenced by spatial attention demonstrating that visual, motor, and attentional responses can occur in combination in single neurons of V6A. This modulation in an area primarily involved in visuo-motor transformation for reaching suggests that also reach-related regions could directly contribute in the shifts of spatial attention necessary to plan and control goal-directed arm movements. Moreover, to test whether V6A is causally involved in these processes, we have performed a human study using on-line repetitive transcranial magnetic stimulation over the putative human V6A (pV6A) during an attention and a reaching task requiring covert shifts of attention and reaching movements towards cued targets in space. We demonstrate that the pV6A is causally involved in attention reorienting to target detection and that this process interferes with the execution of reaching movements towards unattended targets. The current findings suggest the direct involvement of the action-related dorso-medial visual stream in attentional processes, and a more specific role of V6A in attention reorienting. Therefore, we propose that attention signals are used by the V6A to rapidly update the current motor plan or the ongoing action when a behaviorally relevant object unexpectedly appears at an unattended location.

Closed-loop investigation of the dynamical properties of cardiomyocyte electrophysiology by means of Dynamic clamp and Mathematical modelling

The research field of my PhD concerns mathematical modeling and numerical simulation, applied to the cardiac electrophysiology analysis at a single cell level. This is possible thanks to the development of mathematical descriptions of single cellular components, ionic channels, pumps, exchangers and subcellular compartments. Due to the difficulties of vivo experiments on human cells, most of the measurements are acquired in vitro using animal models (e.g. guinea pig, dog, rabbit). Moreover, to study the cardiac action potential and all its features, it is necessary to acquire more specific knowledge about single ionic currents that contribute to the cardiac activity. Electrophysiological models of the heart have become very accurate in recent years giving rise to extremely complicated systems of differential equations. Although describing the behavior of cardiac cells quite well, the models are computationally demanding for numerical simulations and are very difficult to analyze from a mathematical (dynamical-systems) viewpoint. Simplified mathematical models that capture the underlying dynamics to a certain extent are therefore frequently used. The results presented in this thesis have confirmed that a close integration of computational modeling and experimental recordings in real myocytes, as performed by dynamic clamp, is a useful tool in enhancing our understanding of various components of normal cardiac electrophysiology, but also arrhythmogenic mechanisms in a pathological condition, especially when fully integrated with experimental data.

Studies on the Hippo Pathway: new insights about a multifaceted signalling

The Hippo pathway is a well-known master regulator of cell growth and proliferation. Many studies have shed light on the centrality of Hippo functions, as this signalling is able to respond to different stimuli and translate them into distinct transcriptional outputs. Therefore, it is clearly implicated in a number of important processes, which alteration has consequences on the correct specification of the single cell, as well as the whole tissue. Even if the core of the signalling has been extensively characterized, it remains unclear which are the “co-workers” that permit the Hippo pathway to answer to so many different stimuli and act as a coordinator of the growth/differentiation balance. Taking advantage of the Drosophila model, which has witnessed most of the discoveries on this signalling pathway, this thesis aims to add some new knowledge about the Hippo pathway molecular mechanisms in different contexts, from development to disease. In the first part I studied the dynamics of the Hippo core kinase protein Warts in the development of the pupal eye. I have found out a critical time point in which the expression and the localization of Warts change suddenly, suggesting the intervention of upstream regulators modulating its activity in an extremely narrow time window. The second goal was investigating the role of the Hippo pathway in the neurodegenerative Gaucher disease. Indeed, I have produced some preliminary results which demonstrate a growth deficit associated with a massive reduction of some Yki targets, supporting a Hyper-Hippo condition underlying this neuropathic syndrome. Finally, I have evaluated the transcription factor Orthodenticle as a co-factor of Yorkie in driving tissue overgrowth, and my findings support a model of interaction of these two molecules based on Yki conformational changes. Altogether, my results lay the foundation for new important studies on the molecular mechanisms ruling Hippo pathway activity.

Interpretable Convolutional Neural Networks for Decoding and Analyzing Neural Time Series Data

Machine learning is widely adopted to decode multi-variate neural time series, including electroencephalographic (EEG) and single-cell recordings. Recent solutions based on deep learning (DL) outperformed traditional decoders by automatically extracting relevant discriminative features from raw or minimally pre-processed signals. Convolutional Neural Networks (CNNs) have been successfully applied to EEG and are the most common DL-based EEG decoders in the state-of-the-art (SOA). However, the current research is affected by some limitations. SOA CNNs for EEG decoding usually exploit deep and heavy structures with the risk of overfitting small datasets, and architectures are often defined empirically. Furthermore, CNNs are mainly validated by designing within-subject decoders. Crucially, the automatically learned features mainly remain unexplored; conversely, interpreting these features may be of great value to use decoders also as analysis tools, highlighting neural signatures underlying the different decoded brain or behavioral states in a data-driven way. Lastly, SOA DL-based algorithms used to decode single-cell recordings rely on more complex, slower to train and less interpretable networks than CNNs, and the use of CNNs with these signals has not been investigated. This PhD research addresses the previous limitations, with reference to P300 and motor decoding from EEG, and motor decoding from single-neuron activity. CNNs were designed light, compact, and interpretable. Moreover, multiple training strategies were adopted, including transfer learning, which could reduce training times promoting the application of CNNs in practice. Furthermore, CNN-based EEG analyses were proposed to study neural features in the spatial, temporal and frequency domains, and proved to better highlight and enhance relevant neural features related to P300 and motor states than canonical EEG analyses. Remarkably, these analyses could be used, in perspective, to design novel EEG biomarkers for neurological or neurodevelopmental disorders. Lastly, CNNs were developed to decode single-neuron activity, providing a better compromise between performance and model complexity.

Development of unsupervised learning methods with applications to life sciences data

Machine Learning makes computers capable of performing tasks typically requiring human intelligence. A domain where it is having a considerable impact is the life sciences, allowing to devise new biological analysis protocols, develop patients’ treatments efficiently and faster, and reduce healthcare costs. This Thesis work presents new Machine Learning methods and pipelines for the life sciences focusing on the unsupervised field. At a methodological level, two methods are presented. The first is an “Ab Initio Local Principal Path” and it is a revised and improved version of a pre-existing algorithm in the manifold learning realm. The second contribution is an improvement over the Import Vector Domain Description (one-class learning) through the Kullback-Leibler divergence. It hybridizes kernel methods to Deep Learning obtaining a scalable solution, an improved probabilistic model, and state-of-the-art performances. Both methods are tested through several experiments, with a central focus on their relevance in life sciences. Results show that they improve the performances achieved by their previous versions. At the applicative level, two pipelines are presented. The first one is for the analysis of RNA-Seq datasets, both transcriptomic and single-cell data, and is aimed at identifying genes that may be involved in biological processes (e.g., the transition of tissues from normal to cancer). In this project, an R package is released on CRAN to make the pipeline accessible to the bioinformatic Community through high-level APIs. The second pipeline is in the drug discovery domain and is useful for identifying druggable pockets, namely regions of a protein with a high probability of accepting a small molecule (a drug). Both these pipelines achieve remarkable results. Lastly, a detour application is developed to identify the strengths/limitations of the “Principal Path” algorithm by analyzing Convolutional Neural Networks induced vector spaces. This application is conducted in the music and visual arts domains.