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TE
Tara Essock-Burns
Scientist
Scientist and Microscopy Core Manager at Arcadia Science
TE
+3
Published: May 03, 2023
Constraining motile microorganisms for live imaging often requires costly microfluidics or optical traps to keep them in view. We used patterned stamps and agar to make versatile, inexpensive “microchambers” and offer a way to predict the right chamber size for a given organism.
Connections
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TE
+7
Published: Jun 23, 2023
We’re crossing C. reinhardtii and C. smithii algae for high-throughput genotype-phenotype mapping. In preparation, we’re comparing the parents to uncover unique species-specific phenotypes.
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SC
TE
Published: Nov 17, 2023
We distilled label-free microscopy data by comparing and implementing feature-detection algorithms. Sobel and Laplacian methods outperformed pixel intensity variance in accuracy.
Connections
Supplements (1): Code v1.0 - GitHub
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TE
+7
Published: May 31, 2024
To test its utility in analyzing biological samples, we built an open-source Raman spectrometer and collected spectra from chilis, beer, and algae. We could stratify samples, classify replicates, and link spectra with quantitative traits of beer (ABV) and chilis (perceived heat).
Connections
Supplements (1): Code and data - GitHub
KC
TE
DM
Published: Nov 06, 2024
Live imaging of swimming cells can yield insight into an organism’s viability and responses to environmental stimuli. We developed a microscopy workflow and image analysis pipeline, SwimTracker, to track motility phenotypes from swimming cells in high throughput.
Connections
Supplements (2): Code v1.1 - GitHub • Data - BioImage Archive
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DM
Published: Dec 14, 2024
We used Chlamydomonas reinhardtii motility mutants with disrupted genes homologous to human SPEF2 or DNALI1 to model spermatogenic failure disorders SPGF43 and SPGF83, respectively. We recovered aspects of wild-type motility in these mutants with a small-scale drug screen.
Connections
Supplements (2): Code v1.0 - GitHub • Microscopy data - BioImage Archive
KC
TE
+5
Published: Jan 08, 2025
We used straightforward microscopy and computational analyses to reproducibly characterize a nematode motility phenotype with interpretable features. This method should be scalable for high-throughput phenotypic screening.
Connections
Supplements (6): Code v1.0 - GitHub • Protocol - Genotyping C. elegans - protocols.io • Protocol - C. elegans culture and maintenance - protocols.io • Protocol - Bleach life-stage synchronization of C. elegans - protocols.io • Protocol - Preparing C. elegans for image acquisition - protocols.io • Imaging data - BioImage Archive
