Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly pathogenic virus that has caused the global COVID-19 pandemic. Tracing the evolution and transmission of the virus is crucial to respond to and control the pandemic through appropriate intervention strategies. This paper reports and analyses genomic mutations in the coding regions of SARS-CoV-2 and their probable protein secondary structure and solvent accessibility changes, which are predicted using deep learning models. Prediction results suggest that mutation D614G in the virus spike protein, which has attracted much attention from researchers, is unlikely to make changes in protein secondary structure and relative solvent accessibility. Based on 6324 viral genome sequences, we create a spreadsheet dataset of point mutations that can facilitate the investigation of SARS-CoV-2 in many perspectives, especially in tracing the evolution and worldwide spread of the virus. Our analysis results also show that coding genes E, M, ORF6, ORF7a, ORF7b and ORF10 are most stable, potentially suitable to be targeted for vaccine and drug development.
Deciphering useful information from electrophysiological data recorded from the brain, in-vivo or in-vitro, is dependent on the capability to analyse spike patterns efficiently and accurately. The spike analysis mechanisms are heavily reliant on the clustering algorithms that enable separation of spike trends based on their spatio-temporal behaviors. Literature review report several clustering algorithms over decades focused on different applications. Although spike analysis algorithms employ only a small subset of clustering algorithms, however, not much work has been reported on the compliance and suitability of such clustering algorithms for spike analysis. In our study, we have attempted to comment on the suitability of available clustering algorithms and performance capacity when exposed to spike analysis. In this regard, the study reports a compatibility evaluation on algorithms previously employed in spike sorting as well as the algorithms yet to be investigated for application in sorting neural spikes. The performance of the algorithms is compared in terms of their accuracy, confusion matrix and accepted validation indices. Three data sets comprising of easy, difficult, and real spike similarity with known ground-truth are chosen for assessment, ensuring a uniform testbed. The procedure also employs two feature-sets, principal component analysis and wavelets. The report also presents a statistical score scheme to evaluate the performance individually and overall. The open nature of the data sets, the clustering algorithms and the evaluation criteria make the proposed evaluation framework widely accessible to the research community. We believe that the study presents a reference guide for emerging neuroscientists to select the most suitable algorithms for their spike analysis requirements.
Understanding Zika virus infection dynamics is essential, as its recent emergence revealed possible devastating neuropathologies in humans, thus causing a major threat to public health worldwide. Recent research allowed breakthrough in our understanding of the virus and host pathogenesis; however, little is known on its impact on its main vector, Aedes aegypti. Here we show how Zika virus targets Aedes aegypti’s neurons and induces changes in its behavior. Results are compared to dengue virus, another flavivirus, which triggers a different pattern of behavioral changes. We used microelectrode array technology to record electrical spiking activity of mosquito primary neurons post infections and discovered that only Zika virus causes an increase in spiking activity of the neuronal network. Confocal microscopy also revealed an increase in synapse connections for Zika virus-infected neuronal networks. Interestingly, the results also showed that mosquito responds to infection by overexpressing glutamate regulatory genes while maintaining virus levels. This neuro-excitation, possibly via glutamate, could contribute to the observed behavioral changes in Zika virus-infected Aedes aegypti females. This study reveals the importance of virus-vector interaction in arbovirus neurotropism, in humans and vector. However, it appears that the consequences differ in the two hosts, with neuropathology in human host, while behavioral changes in the mosquito vector that may be advantageous to the virus.
BackgroundWidespread in the tropics, the mosquito Aedes aegypti is an important vector of many viruses, posing a significant threat to human health. Vector monitoring often requires fecundity estimation by counting eggs laid by female mosquitoes. Traditionally, manual data analyses have been used but this requires a lot of effort and is the methods are prone to errors. An easy tool to assess the number of eggs laid would facilitate experimentation and vector control operations.ResultsThis study introduces a built-in software called ICount allowing automatic egg counting of the mosquito vector, Aedes aegypti. ICount egg estimation compared to manual counting is statistically equivalent, making the software effective for automatic and semi-automatic data analysis. This technique also allows rapid analysis compared to manual methods. Finally, the software has been used to assess p-cresol oviposition choices under laboratory conditions in order to test the system with different egg densities.ConclusionsICount is a powerful tool for fast and precise egg count analysis, freeing experimenters from manual data processing. Software access is free and its user-friendly interface allows easy use by non-experts. Its efficiency has been tested in our laboratory with oviposition dual choices of Aedes aegypti females. The next step will be the development of a mobile application, based on the ICount platform, for vector monitoring surveys in the field.Electronic supplementary materialThe online version of this article (doi:10.1186/s13071-016-1870-1) contains supplementary material, which is available to authorized users.
Aedes aegypti mosquitoes, main vectors for numerous flaviviruses, have olfactory preferences and are capable of olfactory learning especially when seeking their required environmental conditions to lay their eggs. In this study, we showed that semiochemical conditions during Aedes aegypti larval rearing affected future female choice for oviposition: water-reared mosquitoes preferred to lay eggs in water or p-cresol containers, while skatole reared mosquitoes preferred skatole sites. Using two independent behavioural assays, we showed that this skatole preference was lost in mosquitoes infected with dengue virus. Viral RNA was extracted from infected female mosquito heads, and an increase of virus load was detected from 3 to 10 days post infection, indicating replication in the insect head and possibly in the central nervous system. Expression of selected genes, potentially implied in olfactory learning processes, were also altered during dengue infection. Based on these results, we hypothesise that dengue virus infection alters gene expression in the mosquito’s head and is associated with a loss of olfactory preferences, possibly modifying oviposition site choice of female mosquitoes.
BackgroundZika virus infection in new born is linked to congenital syndromes, especially microcephaly. Studies have shown that these neuropathies are the result of significant death of neuronal progenitor cells in the central nervous system of the embryo, targeted by the virus. Although cell death via apoptosis is well acknowledged, little is known about possible pathogenic cellular mechanisms triggering cell death in neurons.MethodsWe used in vitro embryonic mouse primary neuron cultures to study possible upstream cellular mechanisms of cell death. Neuronal networks were grown on microelectrode array and electrical activity was recorded at different times post Zika virus infection. In addition to this method, we used confocal microscopy and Q-PCR techniques to observe morphological and molecular changes after infection.ResultsZika virus infection of mouse primary neurons triggers an early spiking excitation of neuron cultures, followed by dramatic loss of this activity. Using NMDA receptor antagonist, we show that this excitotoxicity mechanism, likely via glutamate, could also contribute to the observed nervous system defects in human embryos and could open new perspective regarding the causes of adult neuropathies.ConclusionsThis model of excitotoxicity, in the context of neurotropic virus infection, highlights the significance of neuronal activity recording with microelectrode array and possibility of more than one lethal mechanism after Zika virus infection in the nervous system.Electronic supplementary materialThe online version of this article (10.1186/s12985-018-0989-4) contains supplementary material, which is available to authorized users.
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