Automated Quantification of Synaptic Fluorescence in <em>C. elegans</em>

Abstract

Synapse strength refers to the amplitude of postsynaptic responses to presynaptic neurotransmitter release events, and has a major impact on overall neural circuit function. Synapse strength critically depends on the abundance of neurotransmitter receptors clustered at synaptic sites on the postsynaptic membrane. Receptor levels are established developmentally, and can be altered by receptor trafficking between surfacelocalized, subsynaptic, and intracellular pools, representing important mechanisms of synaptic plasticity and neuromodulation. Rigorous methods to quantify synaptically-localized neurotransmitter receptor abundance are essential to study synaptic development and plasticity. Fluorescence microscopy is an optimal approach because it preserves spatial information, distinguishing synaptic from non-synaptic pools, and discriminating among receptor populations localized to different types of synapses. The genetic model organism Caenorhabditis elegans is particularly well suited for these studies due to the small size and relative simplicity of its nervous system, its transparency, and the availability of powerful genetic techniques, allowing examination of native synapses in intact animals.Here we present a method for quantifying fluorescently-labeled synaptic neurotransmitter receptors in C. elegans. Its key feature is the automated identification and analysis of individual synapses in three dimensions in multi-plane confocal microscope output files, tabulating position, volume, fluorescence intensity, and total fluorescence for each synapse. This approach has two principal advantages over manual analysis of z-plane projections of confocal data. First, because every plane of the confocal data set is included, no data are lost through z-plane projection, typically based on pixel intensity averages or maxima. Second, identification of synapses is automated, but can be inspected by the experimenter as the data analysis proceeds, allowing fast and accurate extraction of data from large numbers of synapses. Hundreds to thousands of synapses per sample can easily be obtained, producing large data sets to maximize statistical power. Considerations for preparing C. elegans for analysis, and performing confocal imaging to minimize variability between animals within treatment groups are also discussed. Although developed to analyze C. elegans postsynaptic receptors, this method is generally useful for any type of synaptically-localized protein, or indeed, any fluorescence signal that is localized to discrete clusters, puncta, or organelles.The procedure is performed in three steps: 1) preparation of samples, 2) confocal imaging, and 3) image analysis. Steps 1 and 2 are specific to C. elegans, while step 3 is generally applicable to any punctate fluorescence signal in confocal micrographs.

Using Multiple Phenotype Assays and Epistasis Testing to Enhance the Reliability of RNAi Screening and Identify Regulators of Muscle Protein Degradation

“…For example, unc-82 treated animals look relatively wild-type ( Figure 2 B) but move more slowly whereas unc-23 treated animals ( Figure 2 C) often appear to push their heads to one side when moving forward but look relatively normal when moving in reverse. While we did not use automated methods these can be employed to monitor various phenotypes and do so in an easily quantified fashion [ 31 , 32 , 33 , 37 , 38 , 39 , 40 , 41 , 42 , 43 ] thereby also potentially reducing false negatives during RNAi screening.…”

“…Acute treatment of adult worms with RNAi may be beneficial for automation of RNAi screens [31,32,33], as screens could be performed in a set time frame with less need for transferring worms to new food. Our data also suggest that defects in mitochondrial and sarcomere structure can also be determined in acute screens.…”

“…However, it is now clear that one could simply screen adults transferred to RNAi feeder bacteria, to identify potential negative regulators of muscle protein degradation, subject to the caveat that regulators of class (d) above might be missed. Acute treatment of adult worms with RNAi may be beneficial for automation of RNAi screens [ 31 , 32 , 33 ], as screens could be performed in a set time frame with less need for transferring worms to new food. Our data also suggest that defects in mitochondrial and sarcomere structure can also be determined in acute screens.…”

MultiMap: A Tool to Automatically Extract and Analyse Spatial Microscopic Data From Large Stacks of Confocal Microscopy Images

“…The 3D nature of the problem does not allow the use of density estimation techniques such as the density estimation without detection implemented in Ilastik (Sommer et al, 2011 ) and described in Fiaschi et al ( 2012 ); in our case it is important to actually detect the objects, since a single punctum can appear in multiples slices of the stack while the sizes, orientations and distribution of the objects are not known a priori. Others methods such as those presented in Sturt and Bamber ( 2012 ) and Dumitriu et al ( 2012 ) are not fully automatic and require an expert (e.g., to choose an appropriate threshold of the image). Moreover, they rely on thresholding, a global procedure that cannot be applied uniformly over different stacks where objects could be imaged at different intensity.…”