TrypTag is a genome-wide database of the subcellular protein localisation in the unicellular parasite Trypanosoma brucei. The main paper describing this resource is Billington et al., 2023.
Proteins were fluorescently labelled using endogenous tagging with the fluorescent protein mNeonGreen (Shaner et al., 2013) then the tagged cell lines were viewed by diffraction-limited widefield fluorescence microscopy. All tagging was done in the procyclic form.
Wherever possible, we have determine the localisation of the protein by N and C terminal tagging. N terminal tagging of proteins with a predicted signal peptide was avoided, and bear in mind that tagging may disrupt a targeting sequence. The localisation observed for each cell line has been manually annotated using a standardised ontology.
We used long-primer PCR (Dean et al., 2015) to make the tagging constructs and transfected the PCR product into trypanosomes using 96 well electroporation plates (Dyer et al., 2016). The original project aims and full workflow is described in the project announcement mini-review (Dean et al., 2016). The localisation ontology is described in Halliday et al., 2017.
We are keen to see TrypTag used to maximum effect. Please contact us if you have any queries, whether about the methodology and data, help accessing the data or a scientific query you'd like us to help you with.
You can contact us at: email@example.com
Experimental work is now complete, and data analysis for the main paper describing the project is complete. Tagged cell lines 89% of protein coding genes on chromosomal contigs (excluding VSGs) have been successfully generated.
The images and annotations shown on this website are a small fraction of the total data. Larger fields of view and more example cells are also available in the raw data.
The cell lines have not been kept after imaging. It would have been prohibitively costly to store the cell lines and it is rapid to independly remake the cell lines.
TrypTag.org is a quick and easy way to search for protein localisations in TrypTag by gene ID or annotated protein/gene name.
If you use TrypTag in your research, please cite Billington et al., 2023. We recommend including this citation in the results or methods if TrypTag was used as part of a discovery process. If directly using TrypTag images, please also indicate in the figure legend or similar which images are from TrypTag.
Data can be mined via the cellular localization imaging or cellular component GO term searches at the genome database TriTrypDB.org (part of VEuPathDB). If you do so, please also cite the genome database.
All raw data is available at Zenodo (doi:10.5281/zenodo.6862289). This is the data you will need for a custom image analysis or similar. If you do so, please also cite this deposition.
Data from the TrypTag database free to use with acknowledgement by citing the main paper describing the resource, Billington et al., 2023:
To accept these terms and view localisation images and data please click here.
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