I first got involved in this project in 2016, and I gave an oral presentation on this at #USHUPO 2018.
Very fortunate to be part of this worldwide collaborative team, including: California, North Carolina, Wisconsin, Switzerland, and Sweden
This started with Philipp's observation that succinyl-CoA binding proteins of the complex succinyl-CoA ligase (SCL) had higher succinylation than other proteins in the TCA cycle
I normalized the published data to protein relative intensity and found that TCA cycle proteins (near the site of succinyl-CoA production) were more likely to be hypersuccinylated in SIRT5 KO than random chance
We got fibroblasts and myotubes from patients with rare genetic succinyl-CoA ligase deficiency and found that, as expected, they had elevated succinyl-CoA
western blots suggested hyper succinylation in those patient cells, so I did succinyl proteomics analysis on those fibroblasts and myotubes and we found that almost every succinylation site was statistically higher in patient cells
this is also where you can see the magic of graphic designer help (Figure 2):
original figure graphic designer
This is when fluency in R really helped: we wanted to compare the sites we found in human cells to those from Park et all SIRT5 KO in mouse embryonic fibroblasts. I wrote code to align the lysine residues between modified proteins from both human and mouse datasets
Figure 3 compares those datasets. We find that the fold change is much higher in cells from SCL patients versus SIRT5 KO mice. Apples to oranges in many ways but interesting:
original figure graphic designer
Finally, having confirmed the hypersuccinylation was bad in this disease, Philipp made the same mutations in zebrafish, and also made a Sirt5 overexpresser to see if that would help rescue their phenotype despite disrupted TCA cycle
Then they put the fish in a seahorse respirometer! The Sirt5 OE in the SUCLA2 knockout background had higher uncoupled respiration, and it lived longer than the SUCLA2 KO
Thanks to my collaborators for making this possible and making it awesome.
Thanks to the reviewers for their reasonable comments that made the paper better.
This technique forms a central pillar of my labs research
SEEKING POSTDOCS to work in on all aspects of this eco system (applications, data collection, data analysis, and what to do with thousands of proteome profiles we produce?!)