An open source tool for automatic spatiotemporal assessment of calcium transients and local ‘signal-close-to-noise’ activity in calcium imaging data

<div><p>Local and spontaneous calcium signals play important roles in neurons and neuronal networks. Spontaneous or cell-autonomous calcium signals may be difficult to assess because they appear in an unpredictable spatiotemporal pattern and in very small neuronal loci of axons or dendrites. We developed an open source bioinformatics tool for an unbiased assessment of calcium signals in x,y-t imaging series. The tool bases its algorithm on a continuous wavelet transform-guided peak detection to identify calcium signal candidates. The highly sensitive calcium event definition is based on identification of peaks in 1D data through analysis of a 2D wavelet transform surface. For spatial analysis, the tool uses a grid to separate the x,y-image field in independently analyzed grid windows. A document containing a graphical summary of the data is automatically created and displays the loci of activity for a wide range of signal intensities. Furthermore, the number of activity events is summed up to create an estimated total activity value, which can be used to compare different experimental situations, such as calcium activity before or after an experimental treatment. All traces and data of active loci become documented. The tool can also compute the signal variance in a sliding window to visualize activity-dependent signal fluctuations. We applied the calcium signal detector to monitor activity states of cultured mouse neurons. Our data show that both the total activity value and the variance area created by a sliding window can distinguish experimental manipulations of neuronal activity states. Notably, the tool is powerful enough to compute local calcium events and ‘signal-close-to-noise’ activity in small loci of distal neurites of neurons, which remain during pharmacological blockade of neuronal activity with inhibitors such as tetrodotoxin, to block action potential firing, or inhibitors of ionotropic glutamate receptors. The tool can also offer information about local homeostatic calcium activity events in neurites.</p></div

Structures with high rates of local activity after calcium spike blockade.

<p><b>a</b>, Average intensity image of hippocampal neurons loaded with the calcium indicator. Grid windows with high rates of local activity are shown in yellow (see c). <b>b</b>, Activity map (see also <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006054#pcbi.1006054.g008" target="_blank">Fig 8</a>). <b>c</b>, Five regions of interest are indicated (trace 1 –trace 5). The upper three represent growth cone-like structures, the lower two traces represent hotspots on neurites. Note the variability and the diverse character of the calcium signal patterns detected by the computational approach.</p

Overview of image analysis by NA³.

<p><b>a</b>, Motoneuron loaded with a fluorescent calcium indicator. Average intensity projection of 1000 images to show the neuronal morphology. The neuron shifts spontaneously from a low activity state to a high activity state. Rainbow pseudocolor shows low intensity values in blue and high intensity values in red. <b>b</b>, Workflow for the analysis of calcium imaging raw data. After threshold determination according to a rule, the user defines the window size for x,y-grid, and chooses a signal-to-noise ratio value to tune the stringency of the tool. Two computations are started: (1) the signal intensity calculation, (2) the wavelet transform. A result pdf is automatically created. <b>c</b>, The signal-to-noise ratio (SNR) defines the stringency of the computation. The signal average threshold (SAT) can be used to set a signal threshold. The SAT can be close to the black level without having a strong impact on the computation result. <b>d</b>, The documentation pdf defines activity events, marks them, and counts them. All traces showing one or more activity events are given and used to count the total activity. An overview image is created that shows the grid over the first image of the movie, red circles to visualize the activity state of a grid window, and the total activity value, which is a computed value to describe the overall activity state of the neurons. The number of counted activity events per grid window events is shown in a text fil in the results folder. <b>e</b>, Overview of the NA³ workflow. The tool combines functions in ImageJ with “R”. Video processing and signal extraction occurs in ImageJ, before the signals are automatically transferred to “R”. In “R”, the event computing takes place. The result is created in “R” and exported as a pdf-file. The results are also transferred back to ImageJ to allow an interactive access to the data for image processing, ROI selection, or data evaluation.</p

Parallel computing of activity events and variance area.

<p><b>a</b>, Activity map of spontaneous activity of hippocampal neurons (DIV 10) before and after acute activity blockade. <b>b</b>, Calcium spike formation (left trace) is blocked by the inhibitor cocktail (right trace). <b>c—e</b>, Raw traces representing typical calcium signals in non-spiking areas (black trace). The yellow band indicates the variance area in a sliding window of 30 images. Activity marks are indicated as red dots. The activity state of the grid windows is described with two parameters, the variance area, and the number of activity events. <b>c</b>, Signal trace with one or two computed activity events. The variance area is almost identical before and after spike block. <b>d</b>, Signal fluctuations, represented by the variance area, become smaller under spike block conditions. Furthermore, the activity inhibitor cocktail reduces the number of activity events. <b>e</b>, This grid window over a neuritic element shows high signal fluctuation, which correlates with a higher number of activity events. Spike-blockade reduces the variance area and the number of activity events. However, a local activity event is not blocked by the inhibitor cocktail. Structural elements of local activity on the basis of this analysis are shown in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006054#pcbi.1006054.g009" target="_blank">Fig 9</a>.</p

Activity profile of hippocampal neurons after calcium spike blockade.

<p><b>a</b>, Average intensity: Hippocampal neurons loaded with a fluorescent calcium indicator. Pseudocolor images: neurons before a spike, during a calcium spike (seen in the lower left cell), and after spike blockade. 3000 images, acquired at 20Hz are analyzed (WS8, SAT7, SNR 3). <b>b</b>, Under control conditions, one neuron (the lower, left) shows a high spiking activity, as indicated by the activity pattern (red circles in the grid windows). After acute treatment with an inhibitor cocktail (TTX, CNQX, APV), spiking behavior is blocked (yellow squares; traces in c), non-spike-like activity events become visible on the soma and in the periphery. Shape and number of residual activity signals are quite diverse (bright blue squares; traces in c). <b>c</b>; Grid window-specific signal traces with the corresponding activity marks (red) as indicated in b. <b>d</b>, Activity hotspot in the periphery, in a varicosity-like structure. The activity hotspot is indicated by a contrast-enhanced average intensity projection. Image 496 shows the low activity state, while image 2124 indicates the high activity state. The corresponding grid window is indicated in (b).</p

Impaired neuronal maturation of hippocampal neural progenitor cells in mice lacking CRAF

<div><p>RAF kinases are major constituents of the mitogen activated signaling pathway, regulating cell proliferation, differentiation and cell survival of many cell types, including neurons. In mammals, the family of RAF proteins consists of three members, ARAF, BRAF, and CRAF. Ablation of CRAF kinase in inbred mouse strains causes major developmental defects during fetal growth and embryonic or perinatal lethality. Heterozygous germline mutations in CRAF result in Noonan syndrome, which is characterized by neurocognitive impairment that may involve hippocampal physiology. The role of CRAF signaling during hippocampal development and generation of new postnatal hippocampal granule neurons has not been examined and may provide novel insight into the cause of hippocampal dysfunction in Noonan syndrome. In this study, by crossing CRAF-deficiency to CD-1 outbred mice, a CRAF mouse model was established which enabled us to investigate the interplay of neural progenitor proliferation and postmitotic differentiation during adult neurogenesis in the hippocampus. Albeit the general morphology of the hippocampus was unchanged, CRAF-deficient mice displayed smaller granule cell layer (GCL) volume at postnatal day 30 (P30). In CRAF-deficient mice a substantial number of abnormal, chromophilic, fast dividing cells were found in the subgranular zone (SGZ) and hilus of the dentate gyrus (DG), indicating that CRAF signaling contributes to hippocampal neural progenitor proliferation. CRAF-deficient neural progenitor cells showed an increased cell death rate and reduced neuronal maturation. These results indicate that CRAF function affects postmitotic neural cell differentiation and points to a critical role of CRAF-dependent growth factor signaling pathway in the postmitotic development of adult-born neurons.</p></div

Wavelet-based activity detection in noise signals and spike-detection precision in a spontaneous active hippocampal neuron.

<p><b>a</b> Activity distribution under control conditions (movie as in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006054#pcbi.1006054.g004" target="_blank">Fig 4b</a>, left panel). Here, analysis was performed with the following parameters: WS8, SNR 2.5, SAT 2, MAC 1). 4092 activity events were computed. <b>b</b>, Noise video analysis. A homogenous fluorescence signal was imaged (identical camera settings). Analysis was performed with the following parameters: WS8, SNR 2.5, SAT 2, MAC 1). 53 noise events were computed. Some signals are camera-based (graph 31/21). <b>c</b>, Calcium spikes in loci of synchronous activity. Loci are marked in (a). All cell soma ROI (magenta) was computed with the ROI tool in NA³.<b>d</b>, Typical signal traces found in the noise video. Grid windows are indicated in (b). <b>e</b>, Spike-detection precision. Areas showing 23 synchronous spikes (1/13–41/23) are compared with a subthreshold SAT value, at different SNR values. The graph shows the underestimation in the number of spikes in the y-axis. <b>f</b>, Comparison of computed events in the noise video (in b) compared to spontaneous active neurons (in a). Settings were: WS8, SNR variable, SAT 2, MAC 1. All SNR values allow the discrimination between the noise state and the active state. The higher the SNR, the better is the stringency of the tool. Small activity events are underestimated under high SNR conditions.</p

Computation of action potential-induced calcium events.

<p>a, Experimental approach. Whole-cell patch clamp recording and parallel calcium imaging of single cells. Here, the calcium indicator was applied with the help of the patch clamp pipette. <b>b,c</b>, Analysis of true-positive responses (TPR) and false-positive responses (FPR) based on parallel calcium imaging and patch clamp recording. Action potentials were induced by current injection (12 times, 200 pA, interstimulus interval: 5 s) for different times (10–500 ms). Current injection of 200 pA for 10 ms (upper panel in c) or 100 ms (lower panel in c) induced single action potentials (indicated by the blue label and vertical line. Calcium imaging was performed at 20 Hz. Calcium event labeling by four computational approaches. Four computational strategies for calcium event definition were applied; our CWT-approach, deconvolution, template-matching, and definition of significant signals above a computed baseline (‘Romano toolbox’). <b>d</b>, Experimental approach. Hippocampal neurons were cultured for 24 days in vitro. At this age, neurons develop glutamatergic synapses with mature hallmarks [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006054#pcbi.1006054.ref039" target="_blank">39</a>] and become spontaneously active. Cells were loaded with OGB1-AM and investigated with patch clamp recording and calcium imaging at 20 Hz. <b>e, f</b>, Electrophysiological recording of action potentials induced by spontaneous activity. In this trace, twelve action potentials are marked and correlate with AP-induced calcium spikes. All twelve calcium events (ROI, cell soma in a) were labeled by the CWT computation under these low SNR conditions.</p

Cell cycle abnormalities in BrdU-labelled NPCs of postnatal CRAF ko mice.

<p>(A) Immuno-histological analysis of BrdU (green) and Ki67 (red) stained sagittal brain sections of CRAF ct and CRAF ko hippocampus at P23 2h after a single BrdU application. Representative brain sections of CRAF ct (upper panel) and CRAF ko (lower panel) show BrdU-labelled cells (green) colocalizing with Ki67 (red) (merge, white arrows). White arrowheads indicate BrdU-labelled cells (green) of CRAF ko that lack any positive Ki67 (red) staining (lower panel). Scale bar = 50μm. (B) Quantitative analysis of BrdU/Ki67-stained proliferative precursor cells in the dentate gyrus (DG) GCL of CRAF ct (dark bar) and CRAF ko (white bar) at P23 (n = 5). The graph shows the fraction of BrdU-labelled cells that lack any positive Ki67 expression 2h after a single BrdU application. Data are mean ± s.e.m.; significant differences are shown in p-value p = 0.0167. (C) Quantitative analysis of BrdU/Ki67-stained proliferative precursor cells in the hilus of CRAF ct (dark bar) and CRAF ko (white bar) at P23 (n = 5). The graph shows the fraction of BrdU-labelled cells that lack any positive Ki67 expression 2h after a single BrdU application. Data are mean ± s.e.m.; significant differences are shown in p-value p = 0.0011. (D) Quantitative analysis of BrdU/Ki67-stained proliferative precursor cells in the dentate gyrus (DG) GCL of CRAF ct (dark bar) and CRAF ko (white bar) at P30 (n = 6). The graph shows the fraction of BrdU-labelled cells that lack any positive Ki67 expression 24h after a single BrdU application. Data are mean ± s.e.m.; significant differences are shown in p-value p<0.0001. (E) Quantitative analysis of BrdU/Ki67-stained proliferative precursor cells in the hilus of CRAF ct (dark bar) and CRAF ko (white bar) at P30 (n = 6). The graph shows the fraction of BrdU-labelled cells that lack any positive Ki67 expression 24h after a single BrdU application. Data are mean ± s.e.m.; significant differences are shown in p-value p = 0.0091.</p

Calcium activity assessment with the activity detector tool.

<p><b>a</b>, Principle of calcium activity event detection. Activity event identification is shown for a representative grid window (per se representing a ROI) on a single motoneuron. This motoneuron (shown in the inlet, and in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006054#pcbi.1006054.g001" target="_blank">Fig 1</a>) shows global calcium transients. 2600 images (frames; x-axis) were analyzed. The grey trace shows the raw mean intensity values of a representative grid window. After extraction of the image signal in a grid window, all local maxima of the intensity signal are identified at several scales (y-axis) and signal candidates are selected and marked (blue dots). Details are explained in the methods: <i>Strategy for calcium event (peak) identification</i>. <b>b</b>, Effect of tuning parameters on calcium activity event detection. The total number of computed activity events (y-axis) in relation to changes in the user-dependent signal-to-noise ratio (SNR). Two activity stages of the motoneuron are compared. The low activity state (<i>in a</i>, frame 1–1300) and the high activity state (frame 1301–2600). Discrimination of the high activity state and the low activity state is very effective over a broad range of SNR values from 1.5 to 4. The signal average threshold was set to an intensity value of 6 (up-rounded mean intensity value seen in the background). A conservative SAT value was selected and modified at a SNR of 2 (blue square; SAT = 5 a.u.; purple circle; SAT = 6 a.u.). <b>c</b>, Data documentation 1: x,y-t summary. The image shows the distribution and number of calcium activity events raised by a spontaneously active motoneuron. Such an image is automatically generated by the program. The user-dependent tuning parameters for this analysis are given. The image field 142 x 130 pixel was automatically split in a grid of 8 x 8 pixel (WS 8 px). Magenta circles indicate areas with calcium events. The smaller the diameter, the less activity is found in the corresponding grid window. All detected calcium activity events are summed up to offer the value ‘total activity’. <b>d</b>, Data documentation 2: the individual traces represent changes in fluorescence in one grid window. The tool automatically generates traces (black line) representing a grid window and shows raw bit values (y-axis) over the frame number (x-axis). Calcium activity events detected by the tool are labeled with a little red square at the peak point. The upper panel describes the graph in grid 5/14 (x/y-axis) in the somatic region of the motoneuron. Here raw bit values ranged from about 65 to 110. In the lower panel a region in the growth cone of the motoneuron was analyzed (grid 13/4; x/y-axis). Here, raw mean bit values in the grid range from 6 to 10. Note the robust detection of global activity despite an almost 10-fold difference in the mean intensity values in the corresponding grid window.</p