EDIT: I was wrong, I was poster 070! 🤦‍♂️

LOL wet! I don't think it's stopped raining for the last 24h ^^

YES! Amazing news, big congrats Rachel! 🎉

Thanks for reading this thread! We hope the paper is interesting and useful Huge thanks to my coauthor @prokaryota.bsky.social for a really cool and enjoyable collab, Elisa is the best :-)

16/16

If your lab does competition assays where microbial antagonism is (or may be!) involved, it might be worth doing a ground-truth check for biases like these. Also, some assays won't be affected e.g. if you use colorimetric killing assays that don't rely on a selection step or c.f.u. counting.

15/n

What's our take-away? Competitive interactions are very common (see e.g. www.science.org/doi/10.1126/...) and we've shown they can be hard to quench in a killing assay. This can lead to over-estimation of strong competitive interactions.

14/n

Conversely, when Susceptible cells are rare (e.g. if they *didn't* do well in the competition assay), few dilutions are required to count Susceptible c.f.u.s. and there will be proportionally more contact with T6SS-armed Attackers. More T6SS contact, more residual killing, fewer c.f.u.s.

13/n

When Susceptible cells are abundant (e.g. if they did pretty well in the competition assay), large dilutions are necessary to count c.f.u.s. These dilutions will tend to separate Attackers and Susceptibles and minimise residual killing on the selective media.

12/n

Why does this bias results most where the Attacker : Susceptible ratio is high?

Here's a little cartoon explainer:

11/n

We also found that, if cell mixtures are pre-incubated in a liquid antibiotic that selects against T6SS attackers, this reduces the bias, especially for longer pre-incubation times.

10/n