This work highlights why genetic background matters in model organisms! Even after multiple rounds of backcrossing, unexpected phenotypes can emerge that may not be directly related to the gene you're studying. @ArcadiaScience [9/9]

To figure this out, we're testing another CPC1 mutant (cpc1-2) from a different genetic background and trying to rescue both with wild-type CPC1 expression. This should tell us if these growth phenotypes are due to the mutation or genetic background. [8/9]

Why does cpc1-1 behave so differently? It might be retaining genetic material from its parent strain despite backcrossing. Or maybe the CPC1 protein itself plays a role in metabolism - it does interact with enolase and other glycolytic enzymes! [7/9]

Third, after 47 days, cpc1-1 was the ONLY strain that could grow on marine medium with high salt content, revealing an unexpected halotolerance. [6/9]

Second, on nitrate-containing media, wild-type C. reinhardtii and ida4 showed chlorosis (yellowing) as expected due to their nit2 mutation. But cpc1-1 maintained dark green colonies, suggesting it can use nitrate efficiently. [5/9]

First, cpc1-1 showed enhanced growth on media with proteose peptone, outperforming wild-type strains that barely grew in this condition! [4/9]

The cpc1-1 mutant (which has defects in the central pair complex of flagella) showed three surprising growth phenotypes that weren't present in other strains, including the ida4 mutant (which has inner dynein arm defects). [3/9]

We were studying flagellar mutants as models for human ciliary diseases when we noticed something odd about their growth patterns. So we decided to compare growth across different media types to see if these mutations affect metabolism beyond just flagellar function. [2/9]

Thanks to the team at @arcadiascience.bsky.social! Especially @taraeb.bsky.social, Ryan Lane, Dave Mets, @meganhoch.bsky.social, & Audrey Bell who made this work possible! Check out the pub here (research.arcadiascience.com/pub/result-chlamy-spgf) & feel free to comment! We love feedback! [8/8]

While this project is now on ice (explained in pub), all code & data are available: 🔗 GitHub: (github.com/Arcadia-Scie...) 📊 BioImage Archive: (www.ebi.ac.uk/biostudies/b...). [7/8]

The different effects of each drug highlight how similar swimming problems can arise from distinct molecular pathways. What works for one genetic variant may not work for another [6/8]

Despite similar motility defects, the mutations responded differently to treatment —- what rescued one mutation often had no effect on the other. This suggests mutation-specific therapeutic approaches are needed [5/8]

We developed two complementary approaches to measure motility: a population "sink-or-swim" assay and detailed single-cell tracking with SwimTracker (research.arcadiascience.com/pub/resource-swimtracker-htp-swimming-assay/release/2). This revealed how drugs affect different aspects of swimming [4/8]

These mutants were characterized decades ago and show similar swimming defects to those seen in SPGF patients' sperm. Our phylogenetic framework showed they're excellent models for SPGF83 and SPGF43 [3/8]

We used phylogenetic analysis from our pub led by Ryan York, Austin Patton & @pracheeac.bsky.social (research.arcadiascience.com/pub/result-evolutionary-organismal-selection) and found Chlamydomonas proteins have high conservation with SPGF proteins. [2/8]

Ryan’s poster:
zenodo.org/doi/10.5281/...

The concept:
research.arcadiascience.com/pub/idea-sel...

The approach and analyses:
research.arcadiascience.com/pub/result-e...

The validation:
research.arcadiascience.com/pub/result-c...