Errors of latency estimation without correction of pixel acquisition time.

<p>Errors of latency estimation without correction of pixel acquisition time.</p

Determination of the accuracy and the precision of the estimated parameters of OG-5N (A, B) and Fluo-3 spikes (C, D).

<p><b>A, C</b> – correlation between the simulated and the fitted parameters (grey circles). Red line is the linear fit. Parameters of the spikes with the bottom 5% of SNR values (2.38±0.04 for OG-5N and 4.33±0.15 for Fluo-3) and of spikes with the top 5% of SNR values (10.11±0.12 for OG-5N and 26.68±0.29 for Fluo-3) are shown as black and blue circles, respectively. Pearson correlation coefficients between the parameters of simulated OG-5N calcium spikes and parameters of their fits were 0.986, 0.893, 0.869 and 0.942 for the A, t₀, TTP and FDHM values, respectively. Pearson correlation coefficients between the parameters of simulated Fluo-3 calcium spikes and parameters of their fits were 0.999, 0.939, 0.962 and 0.993 for the A, t₀, TTP and FDHM values, respectively. <b>B, D</b> – mean ± s.d. of the fitted parameter values grouped by the SNR values of the simulated spikes. Black lines are the mean parameter values of the simulated spikes in the absence of noise. Red lines show mean+s.d. and mean - s.d. of parameter values of noise-free simulated spikes.</p

The measured pixel integration times at different scanning modes and frequencies (Leica TCS SP2 AOBS).

<p>The measured pixel integration times at different scanning modes and frequencies (Leica TCS SP2 AOBS).</p

Description of calcium spikes.

<p>Voltage stimulus from −50 to 0 mV is shown in the top panel. The extracted time course of a calcium spike (black dots) was fitted with the theoretical function (red line, Eq. 1). The latency t₀ was estimated by fitting, and the descriptors were estimated numerically as illustrated. A – peak amplitude, t₀–latency, TTP – time to peak, FDHM – full duration at half maximum.</p

The temporal sequence of pixels in an image acquired in the x-t line scan mode.

<p>Panels A and B describe the unidirectional and the bidirectional mode, respectively, as rendered in the confocal image, that is, each pixel in a line is assigned the same acquisition time. In fact, each subsequent pixel is shifted along the time axis by the value of the pixel integration time, and each line is shifted by the scanner reversal time. Red arrows indicate oscillations of the scanner. The squares represent the acquired pixels of the confocal image; t_ij is the time of acquisition of the pixel in the i^th column and j^th row of the image (<i>i = </i>1 … <i>m</i>, <i>j = </i>1 … <i>n</i>), described by Eq. 3 or Eq. 4 for the unidirectional or the bidirectional mode.</p

Comparison of the parameter values estimated by different fitting procedures.

<p>The Levenberg-Marquardt algorithm in Origin and the Trust-Region algorithm implemented in MATLAB were used on a dataset of 1000 simulated spikes with white noise and normally distributed parameter values. Top row – correlation between parameter values estimated by fitting simulated spikes in Origin and in MATLAB. Middle row – comparison of the fitted parameter values obtained in MATLAB with the input parameter values used in simulations. Bottom row – comparison of the fitted parameter values obtained in Origin with the input parameter values used in simulations. Red lines are linear fits (correlation coefficients are given in Tables S4 in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0064394#pone.0064394.s001" target="_blank">File S1</a>. It should be noted that a majority of the data points lie exactly under the regression lines.</p

Natural selection in bats with historical exposure to white-nose syndrome

Hibernation allows animals to survive periods of resource scarcity by reducing their energy expenditure through decreased metabolism. However, hibernators become susceptible to psychrophilic pathogens if they cannot mount an efficient immune response to infection. While Nearctic bats infected with white-nose syndrome (WNS) suffer high mortality, related Palearctic taxa are better able to survive the disease than their Nearctic counterparts. We hypothesised that WNS exerted historical selective pressure in Palearctic bats, resulting in genomic changes that promote infection tolerance.We investigated partial sequences of 23 genes related to water metabolism and skin structure function in nine Palearctic and Nearctic hibernating bat species and one non-hibernating species for phylogenetic signals of natural selection. Using maximum likelihood analysis, we found that eight genes were under positive selection and we successfully identified amino acid sites under selection in five encoded proteins. Branch site models revealed positive selection in three genes. Hibernating bats exhibit signals for positive selection in genes ensuring tissue regeneration, wound healing and modulation of the immune response.Our results highlight the importance of skin barrier integrity and healing capacity in hibernating bats. The protective role of skin integrity against both pathophysiology and WNS progression, in synergy with down-regulation of the immune reaction in response to the Pseudogymnoascus destructans infection, improves host survival. Our data also suggest that hibernating bat species have evolved into tolerant hosts by reducing the negative impact of skin infection through a set of adaptations, including those at the genomic level

Natural selection in bats with historical exposure to white-nose syndrome

Background Hibernation allows animals to survive periods of resource scarcity by reducing their energy expenditure through decreased metabolism. However, hibernators become susceptible to psychrophilic pathogens if they cannot mount an efficient immune response to infection. While Nearctic bats infected with white-nose syndrome (WNS) suffer high mortality, related Palearctic taxa are better able to survive the disease than their Nearctic counterparts. We hypothesised that WNS exerted historical selective pressure in Palearctic bats, resulting in genomic changes that promote infection tolerance. Results We investigated partial sequences of 23 genes related to water metabolism and skin structure function in nine Palearctic and Nearctic hibernating bat species and one non-hibernating species for phylogenetic signals of natural selection. Using maximum likelihood analysis, we found that eight genes were under positive selection and we successfully identified amino acid sites under selection in five encoded proteins. Branch site models revealed positive selection in three genes. Hibernating bats exhibit signals for positive selection in genes ensuring tissue regeneration, wound healing and modulation of the immune response. Conclusion Our results highlight the importance of skin barrier integrity and healing capacity in hibernating bats. The protective role of skin integrity against both pathophysiology and WNS progression, in synergy with down-regulation of the immune reaction in response to the Pseudogymnoascus destructans infection, improves host survival. Our data also suggest that hibernating bat species have evolved into tolerant hosts by reducing the negative impact of skin infection through a set of adaptations, including those at the genomic level

White-nose syndrome without borders: Pseudogymnoascus destructans infection tolerated in Europe and Palearctic Asia but not in North America

A striking feature of white-nose syndrome, a fungal infection of hibernating bats, is the difference in infection outcome between North America and Europe. Here we show high WNS prevalence both in Europe and on the West Siberian Plain in Asia. Palearctic bat communities tolerate similar fungal loads of Pseudogymnoascus destructans infection as their Nearctic counterparts and histopathology indicates equal focal skin tissue invasiveness pathognomonic for WNS lesions. Fungal load positively correlates with disease intensity and it reaches highest values at intermediate latitudes. Prevalence and fungal load dynamics in Palearctic bats remained persistent and high between 2012 and 2014. Dominant haplotypes of five genes are widespread in North America, Europe and Asia, expanding the source region of white-nose syndrome to non-European hibernacula. Our data provides evidence for both endemicity and tolerance to this persistent virulent fungus in the Palearctic, suggesting that hostpathogen interaction equilibrium has been established