Evidence map›Paper›PMID 42249300›Full record

ArticleBMC bioinformatics2026

Semi-automatic 3D-quantification of in-vivo synapse formation.

Blaž Brence, Laura R Wandelt, Sophie Walter, Stephan J Sigrist, Astrid G Petzoldt, Daniel Baum

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Article in BMC bioinformatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Blaž Brence *Department of Visual and Data-Centric Computing, Zuse Institute Berlin, Takustr. 7, 14195, Berlin, Germany.
Laura R Wandelt *Institute of Biology, Freie Universität Berlin, Takustr. 6, 14195, Berlin, Germany.
Sophie WalterInstitute of Biology, Freie Universität Berlin, Takustr. 6, 14195, Berlin, Germany.
Stephan J SigristInstitute of Biology, Freie Universität Berlin, Takustr. 6, 14195, Berlin, Germany.
Astrid G PetzoldtInstitute of Biology, Freie Universität Berlin, Takustr. 6, 14195, Berlin, Germany. astrid.petzoldt@fu-berlin.de.
Daniel BaumDepartment of Visual and Data-Centric Computing, Zuse Institute Berlin, Takustr. 7, 14195, Berlin, Germany. baum@zib.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSynapses, as specialised cell-cell contacts, allow for a faithful and controlled signal transmission between a neuron and a target cell. Presynapses, the sites of neurotransmitter release, form de novo throughout the development of an organism. Although this process is fundamental to the development and function of synaptic circuits, how developing neurons control number and distribution of individual synapses remains poorly understood. In-vivo imaging analysis of synapse formation at the neuromuscular junction of anaesthetised Drosophila third instar larvae allows for spatial and temporal resolution of the underlying molecular processes. However, high-throughput, comprehensive analysis are hampered by the manual and time-consuming imaging analysis methods applied hitherto. Here, we focus on the early presynaptic formation steps, that is, the presynaptic seeding, initiated by the formation of transient Liprin-α/SYD1 seeding sites, either stabilised or disintegrated over a time span of 30-90 min.

resultsTo investigate the dynamics of the Liprin-α/SYD1 seeding sites, we developed an automated analysis pipeline for 3D confocal images from in-vivo imaging at distinct time points to analyse fluorescently labelled presynaptic protein dynamics during early synapse formation. The workflow is realised in the data analysis software Amira, utilising the hierarchical watershed algorithm, and was designed for automatic processing with an option for manual proofreading. Compared to the previous 2D manual quantification, this automated approach provides a higher sensitivity in single Liprin-α seeding site detection in low-intensity areas and in regions of dense seeding sites. In addition, it substantially reduces the work time. To account for possible errors occurring in the automated processing, we implemented an additional proofreading step allowing for a manual correction of Liprin-α seeding site segmentation and assignment, thus greatly improving the analysis while only marginally increasing work time by 10% to a total work time reduction of 70% compared to the 2D manual analysis paradigm.

conclusionThe process of synaptogenesis underlies the general principles of locomotion, learning and memory formation. The developed fast and accurate semi-automated 3D workflow will provide a substantial progress in the analysis of this molecular process.

Indexed as

Imaging, Three-DimensionalSynapsesAlgorithmsAnimalsDrosophilaNeuromuscular JunctionSoftware3D image analysisIn-vivo imagingLiprin-αNeuromuscular junctionRegistrationSegmentationSemi-automatic workflowSynapse formation

Identifiers

PMID42249300
PMCPMC13251137

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.