Back

Escherichia coli adapts metabolically to 6- and 7-fluoroindole, enabling proteome-wide fluorotryptophan substitution

Treiber-Kleinke, C.; Berger, A.; Adrian, L.; Budisa, N.; Koksch, B.

2023-09-25 synthetic biology
10.1101/2023.09.25.559291 bioRxiv
Show abstract

Nature has scarcely evolved a biochemistry around fluorine. However, modern science proved fluorinated organic molecules to be suitable building blocks for biopolymers, from peptides and proteins up to entire organisms. Here, we conducted adaptive laboratory evolution (ALE) experiments to introduce fluorine into living microorganisms. By cultivating Escherichia coli with fluorinated indole analogues, we successfully evolved microbial cells capable of utilizing either 6-fluoroindole or 7-fluoroindole for growth. Our improved ALE protocols enabled us to overcome previous challenges and achieve consistent and complete adaptation of microbial populations to these unnatural molecules. In the ALE experiments, we supplied fluoroindoles to auxotrophic E. coli bacteria, exerting strong selective pressure that led to microbial adaptation and growth on monofluorinated indoles. Within the cells, these indoles were converted into corresponding amino acids (6- and 7-fluorotryptophan) and incorporated into the proteome at tryptophan sites. This study is a first step and establishes a strong foundation for further exploration of the mechanisms underlying fluorine-based life and how a formerly stressor (fluorinated indole) becomes a vital nutrient. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=64 SRC="FIGDIR/small/559291v1_ufig1.gif" ALT="Figure 1"> View larger version (17K): org.highwire.dtl.DTLVardef@1a3b17org.highwire.dtl.DTLVardef@1d716aorg.highwire.dtl.DTLVardef@10126d5org.highwire.dtl.DTLVardef@9c8a43_HPS_FORMAT_FIGEXP M_FIG C_FIG

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.