Analysis of ion channel stochastic signals for biosensing

In biological world, life of cells is guaranteed by their ability to sense and to respond to a large variety of internal and external stimuli. In particular, excitable cells, like muscle or nerve cells, produce quick depolarizations in response to electrical, mechanical or chemical stimuli: this means that they can change their internal potential through a quick exchange of ions between cytoplasm and the external environment. This can be done thanks to the presence of ion channels, proteins that span the lipid bilayer and act like switches, allowing ionic current to flow opening and shutting in a stochastic way. For a particular class of ion channels, ligand-gated ion channels, the gating processes is strongly influenced by binding between receptive sites located on the channel surface and specific target molecules. These channels, inserted in biomimetic membranes and in presence of a proper electronic system for acquiring and elaborating the electrical signal, could give us the possibility of detecting and quantifying concentrations of specific molecules in complex mixtures from ionic currents across the membrane; in this thesis work, this possibility is investigated. In particular, it reports a description of experiments focused on the creation and the characterization of artificial lipid membranes, the reconstitution of ion channels and the analysis of their electrical and statistical properties. Moreover, after a chapter about the basis of the modelling of the kinetic behaviour of ligand gated ion channels, a possible approach for the estimation of the target molecule concentration, based on a statistical analysis of the ion channel open probability, is proposed. The fifth chapter contains a description of the kinetic characterisation of a ligand gated ion channel: the homomeric α2 isoform of the glycine receptor. It involved both experimental acquisitions and signal analysis. The last chapter represents the conclusions of this thesis, with some remark on the effective performance that may be achieved using ligand gated ion channels as sensing elements.

Molecular analysis of Sigma-1 receptor modulation of the dopamine transporter

Sigma (σ) receptors are well established as a non-opioid, non-phencyclidine, and haloperidol-sensitive receptor family with its own binding profile and a characteristic distribution in the central nervous system (CNS) as well as in endocrine, immune, and some peripheral tissues. Two σ receptors subtypes, termed σ1 and σ2, have been pharmacologically characterized, but, to date, only the σ1 has also been cloned. Activation of σ1 receptors alter several neurotransmitter systems and dopamine (DA) neurotrasmission has been often shown to constitute an important target of σ receptors in different experimental models; however the exact role of σ1 receptor in dopaminergic neurotransmission remains unclear. The DA transporter (DAT) modulates the spatial and temporal aspects of dopaminergic synaptic transmission and interprer the primary mechanism by wich dopaminergic neurons terminate the signal transmission. For this reason present studies have been focused in understanding whether, in cell models, the human subtype of σ1 (hσ1) receptor is able to directly modulate the human DA transporter (hDAT). In the first part of this thesis, HEK-293 and SH-SY5Y cells were permanently transfected with the hσ1 receptor. Subsequently, they were transfected with another plasmid for transiently expressing the hDAT. The hDAT activity was estimated using the described [3H]DA uptake assay and the effects of σ ligands were evaluated by measuring the uptaken [3H]DA after treating the cells with known σ agonists and antagonists. Results illustrated in this thesis demonstrate that activation of overexpressed hσ1 receptors by (+)-pentazocine, the σ1 agonist prototype, determines an increase of 40% of the extracellular [3H]DA uptake, in comparison to non-treated controls and the σ1 antagonists BD-1047 and NE-100 prevent the positive effect of (+)-pentazocine on DA reuptake DA is likely to be considered a neurotoxic molecule. In fact, when levels of intracellular DA abnormally invrease, vescicles can’t sequester the DA which is metabolized by MAO (A and B) and COMT with consequent overproduction of oxygen reactive species and toxic catabolites. Stress induced by these molecules leads cells to death. Thus, for the second part of this thesis, experiments have been performed in order to investigate functional alterations caused by the (+)-pentazocine-mediated increase of DA uptake; particularly it has been investigated if the increase of intracellular [DA] could affect cells viability. Results obtained from this study demonstrate that (+)-pentazocine alone increases DA cell toxicity in a concentration-dependent manner only in cells co-expressing hσ1 and hDAT and σ1 antagonists are able to revert the (+)-pentazocine-induced increase of cell susceptibility to DA toxicity. In the last part of this thesis, the functional cross-talking between hσ1 receptor and hDAT has been further investigated using confocal microscopy. From the acquired data it could be suggested that, following exposure to (+)-pentazocine, the hσ1 receptors massively translocate towards the plasma membrane and colocalize with the hDATs. However, any physical interaction between the two proteins remains to be proved. In conclusion, the presented study shows for the first time that, in cell models, hσ1 receptors directly modulate the hDAT activity. Facilitation of DA uptake induced by (+)-pentazocine is reflected on the increased cell susceptibility to DA toxicity; these effects are prevented by σ1 selective antagonists. Since numerous compounds, including several drugs of abuse, bind to σ1 receptors and activating them could facilitate the damage of dopaminergic neurons, the reported protective effect showed by σ1 antagonists would represent the pharmacological basis to test these compounds in experimental models of dopaminergic neurodegenerative diseases (i.e. Parkinson’s Disease).

Variability analysis of discrete event series and wavefront patterns in surface electrocardiogram: contributions to psychophysiological and clinical research

The surface electrocardiogram (ECG) is an established diagnostic tool for the detection of abnormalities in the electrical activity of the heart. The interest of the ECG, however, extends beyond the diagnostic purpose. In recent years, studies in cognitive psychophysiology have related heart rate variability (HRV) to memory performance and mental workload. The aim of this thesis was to analyze the variability of surface ECG derived rhythms, at two different time scales: the discrete-event time scale, typical of beat-related features (Objective I), and the “continuous” time scale of separated sources in the ECG (Objective II), in selected scenarios relevant to psychophysiological and clinical research, respectively. Objective I) Joint time-frequency and non-linear analysis of HRV was carried out, with the goal of assessing psychophysiological workload (PPW) in response to working memory engaging tasks. Results from fourteen healthy young subjects suggest the potential use of the proposed indices in discriminating PPW levels in response to varying memory-search task difficulty. Objective II) A novel source-cancellation method based on morphology clustering was proposed for the estimation of the atrial wavefront in atrial fibrillation (AF) from body surface potential maps. Strong direct correlation between spectral concentration (SC) of atrial wavefront and temporal variability of the spectral distribution was shown in persistent AF patients, suggesting that with higher SC, shorter observation time is required to collect spectral distribution, from which the fibrillatory rate is estimated. This could be time and cost effective in clinical decision-making. The results held for reduced leads sets, suggesting that a simplified setup could also be considered, further reducing the costs. In designing the methods of this thesis, an online signal processing approach was kept, with the goal of contributing to real-world applicability. An algorithm for automatic assessment of ambulatory ECG quality, and an automatic ECG delineation algorithm were designed and validated.

Analysis of Two Component Systems in Group B Streptococcus Shows that RgfAC and the Novel FspSR Modulate Virulence and Bacterial Fitness

Group B Streptococcus (GBS), in its transition from commensal to pathogen, will encounter diverse host environments and thus require coordinately controlling its transcriptional responses to these changes. This work was aimed at better understanding the role of two component signal transduction systems (TCS) in GBS pathophysiology through a systematic screening procedure. We first performed a complete inventory and sensory mechanism classification of all putative GBS TCS by genomic analysis. Five TCS were further investigated by the generation of knock-out strains, and in vitro transcriptome analysis identified genes regulated by these systems, ranging from 0.1-3% of the genome. Interestingly, two sugar phosphotransferase systems appeared differently regulated in the knock-out mutant of TCS-16, suggesting an involvement in monitoring carbon source availability. High throughput analysis of bacterial growth on different carbon sources showed that TCS-16 was necessary for growth of GBS on fructose-6-phosphate. Additional transcriptional analysis provided further evidence for a stimulus-response circuit where extracellular fructose-6-phosphate leads to autoinduction of TCS-16 with concomitant dramatic up-regulation of the adjacent operon encoding a phosphotransferase system. The TCS-16-deficient strain exhibited decreased persistence in a model of vaginal colonization and impaired growth/survival in the presence of vaginal mucoid components. All mutant strains were also characterized in a murine model of systemic infection, and inactivation of TCS-17 (also known as RgfAC) resulted in hypervirulence. Our data suggest a role for the previously unknown TCS-16, here named FspSR, in bacterial fitness and carbon metabolism during host colonization, and also provide experimental evidence for TCS-17/RgfAC involvement in virulence.

Analysis of earthquakes predictability

Earthquake prediction is a complex task for scientists due to the rare occurrence of high-intensity earthquakes and their inaccessible depths. Despite this challenge, it is a priority to protect infrastructure, and populations living in areas of high seismic risk. Reliable forecasting requires comprehensive knowledge of seismic phenomena. In this thesis, the development, application, and comparison of both deterministic and probabilistic forecasting methods is shown. Regarding the deterministic approach, the implementation of an alarm-based method using the occurrence of strong (fore)shocks, widely felt by the population, as a precursor signal is described. This model is then applied for retrospective prediction of Italian earthquakes of magnitude M≥5.0,5.5,6.0, occurred in Italy from 1960 to 2020. Retrospective performance testing is carried out using tests and statistics specific to deterministic alarm-based models. Regarding probabilistic models, this thesis focuses mainly on the EEPAS and ETAS models. Although the EEPAS model has been previously applied and tested in some regions of the world, it has never been used for forecasting Italian earthquakes. In the thesis, the EEPAS model is used to retrospectively forecast Italian shallow earthquakes with a magnitude of M≥5.0 using new MATLAB software. The forecasting performance of the probabilistic models was compared to other models using CSEP binary tests. The EEPAS and ETAS models showed different characteristics for forecasting Italian earthquakes, with EEPAS performing better in the long-term and ETAS performing better in the short-term. The FORE model based on strong precursor quakes is compared to EEPAS and ETAS using an alarm-based deterministic approach. All models perform better than a random forecasting model, with ETAS and FORE models showing better performance. However, to fully evaluate forecasting performance, prospective tests should be conducted. The lack of objective tests for evaluating deterministic models and comparing them with probabilistic ones was a challenge faced during the study.