ABSTRACT
Quantitative imaging of synaptic vesicle localization and abundance using fluorescently labeled synaptic vesicle associated proteins like GFP::SNB-1 is a well-established method for measuring changes in synapse structure at neuromuscular junctions (NMJ) in C. elegans . To date, however, the ability to easily and reproducibly measure key parameters at the NMJ - maximum intensity, size of GFP::SNB-1 puncta, density of puncta - has relied on the use of expensive, customizable software that requires coding skills to modify, precluding widespread access and thus preventing standardization within the field. We carried out a comparative evaluation of a new, open-source Fiji puncta plugin versus traditional Igor-based analysis of GFP::SNB-1 imaging data taken of cholinergic motor neurons in the dorsal nerve cord of loss of function mutants in fshr-1 , which encodes a G protein-coupled receptor known to impact GFP::SNB-1 accumulation. We analyzed images taken on a widefield fluorescence microscope, as well as on a spinning disk confocal microscope. Our data demonstrate strong concordance between the differences in GFP::SNB-1 localization in fshr-1 mutants compared to wild type worms across both analysis platforms (Fiji and Igor), as well as across microscope types (widefield and confocal). These data also agree with previously published observations related to synapse number and GFP::SNB-1 intensity in fshr-1 and wild type worms. Based on these findings, we conclude that the Fiji platform is viable as a method for analyzing synaptic vesicle localization and abundance at cholinergic dorsal nerve cord motor NMJs and expect the Fiji puncta plugin to be of broad utility in imaging across a variety of imaging platforms and synaptic markers.
ABSTRACT
Understanding the cell biology of protein trafficking and homeostasis requires reproducible methods for identifying and quantifying proteins within cells or cellular structures. Imaging protocols for measuring punctate protein accumulation in linear structures, for example the neurites of C. elegans, have relied on proprietary software for a full range of analysis capabilities. Here we describe a set of macros written for the NIH-supported imaging software ImageJ or Fiji (Fiji is Just ImageJ) that reliably identify protein puncta so that they can be analyzed with respect to intensity, density, and width at half-maximum intensity (Full-Width, Half-Maximum, FWHM). We provide an explanation of the workflow, data outputs, and limitations of the Fiji macro. As part of this integration, we also provide two independent data sets with side-by-side analyses using the proprietary IgorPro software and the Fiji macro (Hulsey-Vincent, et al. A, B., 2023 submitted). The Fiji macro is an important new tool because it provides robust, reproducible data analysis in a free, open-source format.
ABSTRACT
In C. elegans, DAF-7/TGF-beta signaling regulates development, metabolism, and behavior. In addition loss of daf-7 leads to an increase of the glutamate receptor GLR-1. In daf-7(e1372) mutants, GLR-1 tagged with GFP (GLR-1::GFP) accumulates in wide puncta along the ventral nerve cord of the animal. Previous automated analyses of GLR-1::GFP accumulation relied on the proprietary software, IgorPro, for measurement of GLR-1::GFP puncta size, intensity, and density. We did a side-by-side comparison of analyses by IgorPro and an open source macro written for Fiji to analyze images from animals expressing GLR-1::GFP in wild type and daf-7(e1372) backgrounds. Analyses by the two programs were in strong agreement and are in accordance with previously published data on the effects of daf-7(e1372) on GLR-1::GFP accumulation. Based on these data, we conclude that the Fiji platform is a robust method for analyzing the accumulation of a fluorescently-tagged neurotransmitter receptor and that the Fiji puncta plugin will be applicable for image analysis for other neural markers.
ABSTRACT
Course-based undergraduate research experiences (CUREs) provide the same benefits as individual, mentored faculty research while expanding the availability of research opportunities. One important aspect of CUREs is students' engagement in collaboration. The shift to online learning during the COVID-19 pandemic created an immediate need for meaningful, collaborative experiences in CUREs. We developed a partnership with the Caenorhabditis elegans (C. elegans) database, WormBase, in which students submitted annotations of published manuscripts to the website. Due to the stress on students during this time of crisis, qualitative data were collected in lieu of quantitative pre- and postanalyses. Most students reported on cognitive processes that represent mid-level Bloom's categories. By partnering with WormBase, students gained insight into the scientific community and contributed as community members. We describe possible modifications for future courses, potential expansion of the WormBase collaboration, and future directions for quantitative analysis.
