Using RNA-seq to determine the transcriptional landscape and the hypoxic response of the pathogenic yeast Candida parapsilosis

<p>Abstract</p> <p>Background</p> <p><it>Candida parapsilosis </it>is one of the most common causes of <it>Candida </it>infection worldwide. However, the genome sequence annotation was made without experimental validation and little is known about the transcriptional landscape. The transcriptional response of <it>C. parapsilosis </it>to hypoxic (low oxygen) conditions, such as those encountered in the host, is also relatively unexplored.</p> <p>Results</p> <p>We used next generation sequencing (RNA-seq) to determine the transcriptional profile of <it>C. parapsilosis </it>growing in several conditions including different media, temperatures and oxygen concentrations. We identified 395 novel protein-coding sequences that had not previously been annotated. We removed > 300 unsupported gene models, and corrected approximately 900. We mapped the 5' and 3' UTR for thousands of genes. We also identified 422 introns, including two introns in the 3' UTR of one gene. This is the first report of 3' UTR introns in the Saccharomycotina. Comparing the introns in coding sequences with other species shows that small numbers have been gained and lost throughout evolution. Our analysis also identified a number of novel transcriptional active regions (nTARs). We used both RNA-seq and microarray analysis to determine the transcriptional profile of cells grown in normoxic and hypoxic conditions in rich media, and we showed that there was a high correlation between the approaches. We also generated a knockout of the <it>UPC2 </it>transcriptional regulator, and we found that similar to <it>C. albicans</it>, Upc2 is required for conferring resistance to azole drugs, and for regulation of expression of the ergosterol pathway in hypoxia.</p> <p>Conclusion</p> <p>We provide the first detailed annotation of the <it>C. parapsilosis </it>genome, based on gene predictions and transcriptional analysis. We identified a number of novel ORFs and other transcribed regions, and detected transcripts from approximately 90% of the annotated protein coding genes. We found that the transcription factor Upc2 role has a conserved role as a major regulator of the hypoxic response in <it>C. parapsilosis </it>and <it>C. albicans</it>.</p

25th annual computational neuroscience meeting: CNS-2016

The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong

A Defined Heteromeric KV1 Channel Stabilizes the Intrinsic Pacemaking and Regulates the Efferent Code of Deep Cerebellar Nuclear Neurons to Thalamic Targets

The output of the cerebellum to the motor axis of the central nervous system is orchestrated mainly by synaptic inputs and intrinsic pacemaker activity of deep cerebellar nuclear (DCN) projection neurons. Herein, we demonstrate that the soma of these cells is enriched with KV1 channels produced by mandatory multi-merization of KV1.1, 1.2 α and KV β2 subunits. Being constitutively active, the K+ current (IKV1) mediated by these channels stabilizes the rate and regulates the temporal precision of self-sustained firing of these neurons. Placed strategically, IKV1 provides a powerful counter-balance to prolonged depolarizing inputs, attenuates the rebound excitation, and dampens the membrane potential bi-stability. Somatic location with low activation threshold render IKV1 instrumental in voltage-dependent de-coupling of the axon initial segment from the cell body of projection neurons, impeding invasion of backpropagating initial segment action potentials into the somato-dendr itic compartment. The latter also promotes the dominance of clock like somatic pace-making in driving the regenerative firing activity of these neurons, to encode time variant inputs with high fidelity. Through the use of multi-compartmental modeling and retro-axonal labeling, the physiological significance of the described functions for processing and communication of information from the lateral DCN to thalamic relay nuclei is establishedPeer reviewedFinal Accepted Versio

Interoperability of neuroscience modeling software: Current status and future directions

Neuroscience increasingly uses computational models to assist in the exploration and interpretation of complex phenomena. As a result, considerable effort is invested in the development of software tools and technologies for numerical simulations and for the creation and publication of models. The diversity of related tools leads to the duplication of effort and hinders model reuse. Development practices and technologies that support interoperability between software systems therefore play an important role in making the modeling process more efficient and in ensuring that published models can be reliably and easily reused. Various forms of interoperability are possible including the development of portable model description standards, the adoption of common simulation languages or the use of standardized middleware. Each of these approaches finds applications within the broad range of current modeling activity. However more effort is required in many areas to enable new scientific questions to be addressed. Here we present the conclusions of the "Neuro-IT Interoperability of Simulators" workshop, held at the 11th computational neuroscience meeting in Edinburgh (July 19-20 2006; http://www.cnsorg.org). We assess the current state of interoperability of neural simulation software and explore the future directions that will enable the field to advance