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Neuronal hyperexcitability is a feature of Alzheimer’s disease (AD). Three main mechanisms have been proposed to explain it: i), dendritic degeneration leading to increased input resistance, ii), ion channel changes leading to enhanced intrinsic excitability, and iii), synaptic changes leading to excitation-inhibition (E/I) imbalance. However, the relative contribution of these mechanisms is not fully understood. Therefore, we performed biophysically realistic multi-compartmental modelling of excitability in reconstructed CA1 pyramidal neurons of wild-type and APP/PS1 mice, a well-established animal model of AD. We show that, for synaptic activation, the excitability promoting effects of dendritic degeneration are cancelled out by excitability decreasing effects of synaptic loss. We find an interesting balance of excitability regulation with enhanced degeneration in the basal dendrites of APP/PS1 cells potentially leading to increased excitation by the apical but decreased excitation by the basal Schaffer collateral pathway. Furthermore, our simulations reveal that three additional pathomechanistic scenarios can account for the experimentally observed increase in firing and bursting of CA1 pyramidal neurons in APP/PS1 mice. Scenario 1: increased excitatory burst input; scenario 2: enhanced E/I ratio and scenario 3: alteration of intrinsic ion channels (IAHP down-regulated; INap, INa and ICaT up-regulated) in addition to enhanced E/I ratio. Our work supports the hypothesis that pathological network and ion channel changes are major contributors to neuronal hyperexcitability in AD. Overall, our results are in line with the concept of multi-causality and degeneracy according to which multiple different disruptions are separately sufficient but no single disruption is necessary for neuronal hyperexcitability.
Reducing neuronal size results in less cell membrane and therefore lower input conductance. Smaller neurons are thus more excitable as seen in their voltage responses to current injections in the soma. However, the impact of a neuron’s size and shape on its voltage responses to synaptic activation in dendrites is much less understood. Here we use analytical cable theory to predict voltage responses to distributed synaptic inputs and show that these are entirely independent of dendritic length. For a given synaptic density, a neuron’s response depends only on the average dendritic diameter and its intrinsic conductivity. These results remain true for the entire range of possible dendritic morphologies irrespective of any particular arborisation complexity. Also, spiking models result in morphology invariant numbers of action potentials that encode the percentage of active synapses. Interestingly, in contrast to spike rate, spike times do depend on dendrite morphology. In summary, a neuron’s excitability in response to synaptic inputs is not affected by total dendrite length. It rather provides a homeostatic input-output relation that specialised synapse distributions, local non-linearities in the dendrites and synaptic plasticity can modulate. Our work reveals a new fundamental principle of dendritic constancy that has consequences for the overall computation in neural circuits.
The electrical and computational properties of neurons in our brains are determined by a rich repertoire of membrane-spanning ion channels and elaborate dendritic trees. However, the precise reason for this inherent complexity remains unknown. Here, we generated large stochastic populations of biophysically realistic hippocampal granule cell models comparing those with all 15 ion channels to their reduced but functional counterparts containing only 5 ion channels. Strikingly, valid parameter combinations in the full models were more frequent and more stable in the face of perturbations to channel expression levels. Scaling up the numbers of ion channels artificially in the reduced models recovered these advantages confirming the key contribution of the actual number of ion channel types. We conclude that the diversity of ion channels gives a neuron greater flexibility and robustness to achieve target excitability.
SARS-CoV-2 infections are rapidly spreading around the globe. The rapid development of therapies is of major importance. However, our lack of understanding of the molecular processes and host cell signaling events underlying SARS-CoV-2 infection hinder therapy development. We employed a SARS-CoV-2 infection system in permissible human cells to study signaling changes by phospho-proteomics. We identified viral protein phosphorylation and defined phosphorylation-driven host cell signaling changes upon infection. Growth factor receptor (GFR) signaling and downstream pathways were activated. Drug-protein network analyses revealed GFR signaling as key pathway targetable by approved drugs. Inhibition of GFR downstream signaling by five compounds prevented SARS-CoV-2 replication in cells, assessed by cytopathic effect, viral dsRNA production, and viral RNA release into the supernatant. This study describes host cell signaling events upon SARS-CoV-2 infection and reveals GFR signaling as central pathway essential for SARS-CoV-2 replication. It provides with novel strategies for COVID-19 treatment.
The measurement of protein dynamics by proteomics to study cell remodeling has seen increased attention over the last years. This development is largely driven by a number of technological advances in proteomics methods. Pulsed stable isotope labeling in cell culture (SILAC) combined with tandem mass tag (TMT) labeling has evolved as a gold standard for profiling protein synthesis and degradation. While the experimental setup is similar to typical proteomics experiments, the data analysis proves more difficult: After peptide identification through search engines, data extraction requires either custom scripted pipelines or tedious manual table manipulations to extract the TMT-labeled heavy and light peaks of interest. To overcome this limitation, which deters researchers from using protein dynamic proteomics, we developed a user-friendly, browser-based application that allows easy and reproducible data analysis without the need for scripting experience. In addition, we provide a python package that can be implemented in established data analysis pipelines. We anticipate that this tool will ease data analysis and spark further research aimed at monitoring protein translation and degradation by proteomics.
The survivin suppressant YM155 is a drug candidate for neuroblastoma. Here, we tested YM155 in 101 neuroblastoma cell lines (19 parental cell lines, 82 drug-adapted sublines). 77 cell lines displayed YM155 IC50s in the range of clinical YM155 concentrations. ABCB1 was an important determinant of YM155 resistance. The activity of the ABCB1 inhibitor zosuquidar ranged from being similar to that of the structurally different ABCB1 inhibitor verapamil to being 65-fold higher. ABCB1 sequence variations may be responsible for this, suggesting that the design of variant-specific ABCB1 inhibitors may be possible. Further, we showed that ABCC1 confers YM155 resistance. Previously, p53 depletion had resulted in decreased YM155 sensitivity. However, TP53-mutant cells were not generally less sensitive to YM155 than TP53 wild-type cells in this study. Finally, YM155 cross-resistance profiles differed between cells adapted to drugs as similar as cisplatin and carboplatin. In conclusion, the large cell line panel was necessary to reveal an unanticipated complexity of the YM155 response in neuroblastoma cell lines with acquired drug resistance. Novel findings include that ABCC1 mediates YM155 resistance and that YM155 cross-resistance profiles differ between cell lines adapted to drugs as similar as cisplatin and carboplatin.
SARS-CoV-2 is a novel coronavirus currently causing a pandemic. We show that the majority of amino acid positions, which differ between SARS-CoV-2 and the closely related SARS-CoV, are differentially conserved suggesting differences in biological behaviour. In agreement, novel cell culture models revealed differences between the tropism of SARS-CoV-2 and SARS-CoV. Moreover, cellular ACE2 (SARS-CoV-2 receptor) and TMPRSS2 (enables virus entry via S protein cleavage) levels did not reliably indicate cell susceptibility to SARS-CoV-2. SARS-CoV-2 and SARS-CoV further differed in their drug sensitivity profiles. Thus, only drug testing using SARS-CoV-2 reliably identifies therapy candidates. Therapeutic concentrations of the approved protease inhibitor aprotinin displayed anti-SARS-CoV-2 activity. The efficacy of aprotinin and of remdesivir (currently under clinical investigation against SARS-CoV-2) were further enhanced by therapeutic concentrations of the proton pump inhibitor omeprazole (aprotinin 2.7-fold, remdesivir 10-fold). Hence, our study has also identified anti-SARS-CoV-2 therapy candidates that can be readily tested in patients.
Resistance to systemic drug therapy is a major reason for the failure of anticancer therapies. Here, we tested doxorubicin-loaded human serum albumin (HSA) nanoparticles in the neuroblastoma cell line UKF-NB-3 and its ABCB1-expressing sublines adapted to vincristine (UKF-NB-3rVCR1) and doxorubicin (UKF-NB-3rDOX20). Doxorubicin-loaded nanoparticles displayed increased anticancer activity in UKF-NB-3rVCR1 and UKF-NB-3rDOX20 cells relative to doxorubicin solution, but not in UKF-NB-3 cells. UKF-NB-3rVCR1 cells were re-sensitised by nanoparticle-encapsulated doxorubicin to the level of UKF-NB-3 cells. UKF-NB-3rDOX20 cells displayed a more pronounced resistance phenotype than UKF-NB-3rVCR1 cells and were not re-sensitised by doxorubicin-loaded nanoparticles to the level of parental cells. ABCB1 inhibition using zosuquidar resulted in similar effects like nanoparticle incorporation, indicating that doxorubicin-loaded nanoparticles successfully circumvent ABCB1-mediated drug efflux. The limited re-sensitisation of UKF-NB-3rDOX20 cells to doxorubicin by circumvention of ABCB1-mediated efflux is probably due to the presence of multiple doxorubicin resistance mechanisms. So far, ABCB1 inhibitors have failed in clinical trials probably because systemic ABCB1 inhibition results in a modified body distribution of its many substrates including drugs, xenobiotics, and other molecules. HSA nanoparticles may provide an alternative, more specific way to overcome transporter-mediated resistance.
Doxorubicin-loaded human serum albumin nanoparticles overcome transporter-mediated drug resistance
(2019)
Resistance to systemic drug therapies is a major reason for the failure of anti-cancer therapies. Here, we tested doxorubicin-loaded human serum albumin (HSA) nanoparticles in the neuroblastoma cell line UKF-NB-3 and its ABCB1-expressing sublines adapted to vincristine (UKF-NB-3rVCR1) and doxorubicin (UKF-NB-3rDOX20). Doxorubicin-loaded nanoparticles displayed increased anti-cancer activity in UKF-NB-3rVCR1 and UKF-NB-3rDOX20 cells relative to doxorubicin solution, but not in UKF-NB-3 cells. UKF-NB-3rVCR1 cells were resensitised by nanoparticle-encapsulated doxorubicin to the level of UKF-NB-3 cells. UKF-NB-3rDOX20 cells displayed a more pronounced resistance phenotype than UKF-NB-3rVCR1 cells and were not re-sensitised by doxorubicin-loaded nanoparticles to the level of parental cells. ABCB1 inhibition using zosuquidar resulted in similar effects like nanoparticle incorporation, indicating that doxorubicin-loaded nanoparticles circumvent ABCB1-mediated drug efflux. The limited re-sensitisation of UKF-NB-3rDOX20 cells to doxorubicin by circumvention of ABCB1-mediated efflux is probably due to the presence of multiple doxorubicin resistance mechanisms. So far, ABCB1 inhibitors have failed in clinical trials, probably because systemic ABCB1 inhibition results in a modified body distribution of its many substrates including drugs, xenobiotics, and other molecules. HSA nanoparticles may provide an alternative, more specific way to overcome transporter-mediated resistance.
SARS-CoV-2 is the causative agent of COVID-19. Severe COVID-19 disease has been associated with disseminated intravascular coagulation and thrombosis, but the mechanisms underlying COVID-19-related coagulopathy remain unknown. Since the risk of severe COVID-19 disease is higher in males than in females and increases with age, we combined proteomics data from SARS-CoV-2-infected cells with human gene expression data from the Genotype-Tissue Expression (GTEx) database to identify gene products involved in coagulation that change with age, differ in their levels between females and males, and are regulated in response to SARS-CoV-2 infection. This resulted in the identification of transferrin as a candidate coagulation promoter, whose levels increases with age and are higher in males than in females and that is increased upon SARS-CoV-2 infection. A systematic investigation of gene products associated with the GO term “blood coagulation” did not reveal further high confidence candidates, which are likely to contribute to COVID-19-related coagulopathy. In conclusion, the role of transferrin should be considered in the course of COVID-19 disease and further examined in ongoing clinic-pathological investigations.