It's a wild mechanism and we had a good time unravelling it using some interesting approaches including using CRISPR integrases to 'catch' the reverse transcribed DNA and triggering this retron using DNA made by a Type II retron

@biorxiv-bioeng.bsky.social @biorxiv-synthbio.bsky.social @mitowomen.bsky.social @biorxiv-molbio.bsky.social

Tons of tricks (like AND gates to add a temporal component) many molecular signals recorded (hypoxia, NF-kB, BMP, Wnt), and demonstrated use for investigating cell fate in a mesoderm differentiation (w/ Nikolaos Poulis & Deepak Srivastava). Take a look, we hope you see a use in your own work.

Since there are so many copies of the mtDNA per cell, each cell carries its own analog recording where a weak signal leads to a small percentage of edited mtDNA and a strong signal leads to a high percentage. Can be prepped and read out along with transcriptomes using a 10x workflow. (more below)

Yep! A core set of plasmids is already going through QC at Addgene for distribution along with full sequence maps and cloning instructions. Addgene numbers are in Supplemental Table 4. I'll add a new post here when they're ready to ship.

Ching-Chung Ko, Graham Hatfull:
M. smegmatis (6%)

@nastassiakn.bsky.social, @marcguellc.bsky.social‬:
C. acnes (0.02%)

Yassir Lekbach, Zihan Yu, Keith Keitz:
S. oneidensis (98%)
P. putida (0.2%)

Heema Selvakumar, @vivekmutalik.bsky.social:
A. baylyi (0.2%)

Jee-Hwan Oh, Jan-Peter van Pijkeren:
L. reuteri (0.1%)

Laura Bonillo-Lopez, Virginia Aragón:
S. suis (0.1%)

Alejandro González-Delgado:
C. freundii (22%)
K. pneumoniae (22%)
P. aeruginosa (7%)

Milo Johnson, @bkoskella.bsky.social:
E. amylovora (4%)
P. syringae (0.7%)

Michael Wold, ‪@bacteriality.bsky.social‬:
V. natrigens (45%)
A. hidrophyla (26%)

Everyone ran the editing in their own favorite species. Of the 15 species (incl E. coli) we found editing above 20% in six of them, above 40% in three of them, and above 90% in two of them. New species and collaborators follow with retron recombineering editing rates:

We didn't in this case, just tested a small edit to see if they were functional. It is nice to have a large stable of retron editors, which will likely have properties that affect the types of edits they make or the cellular context in which they work well. This adds a few more to that stable.

There aren't too many natural retron hosts around, so if you're interested in researching retrons in their real context, let me know and we'll be happy to share these hosts.

Kazuo Nakamura went out and collected bacteria and, with Karen Zhang and Matias Rojas-Montero, found and characterized the retrons in the lab. Mario Mestre (@pentamorfico.bsky.social) helped us understand a weird retron system that had not previously been described.