Parallel engineering of environmental bacteria and performance over years under jungle-simulated conditions
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journal.pone.0278471.pdf
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Published version
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2.95 MB
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Author(s) • • • • • • • •
Chemla, Yonatan
Dorfan, Yuval
Yannai, Adi
Meng, Dechuan
Cao, Paul
Glaven, Sarah
Gordon, D Benjamin
Elbaz, Johann
Voigt, Christopher A
Date Issued
2022
Journal
PLOS ONE
Publisher
Public Library of Science (PLoS)
Citation
Chemla, Yonatan, Dorfan, Yuval, Yannai, Adi, Meng, Dechuan, Cao, Paul et al. 2022. "Parallel engineering of environmental bacteria and performance over years under jungle-simulated conditions." PLOS ONE, 17 (12).
Version
Final published version
Abstract
Engineered bacteria could perform many functions in the environment, for example, to remediate pollutants, deliver nutrients to crops or act as in-field biosensors. Model organisms can be unreliable in the field, but selecting an isolate from the thousands that naturally live there and genetically manipulating them to carry the desired function is a slow and uninformed process. Here, we demonstrate the parallel engineering of isolates from environmental samples by using the broad-host-range XPORT conjugation system (Bacillus subtilis mini-ICEBs1) to transfer a genetic payload to many isolates in parallel. Bacillus and Lysinibacillus species were obtained from seven soil and water samples from different locations in Israel. XPORT successfully transferred a genetic function (reporter expression) into 25 of these isolates. They were then screened to identify the best-performing chassis based on the expression level, doubling time, functional stability in soil, and environmentally-relevant traits of its closest annotated reference species, such as the ability to sporulate and temperature tolerance. From this library, we selected Bacillus frigoritolerans A3E1, re-introduced it to soil, and measured function and genetic stability in a contained environment that replicates jungle conditions. After 21 months of storage, the engineered bacteria were viable, could perform their function, and did not accumulate disruptive mutations.
MIT Department
Massachusetts Institute of Technology. Synthetic Biology Center
Massachusetts Institute of Technology. Department of Biological Engineering
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Creative Commons Attribution 4.0 International license
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DOI of Published Version
https://doi.org/10.1371/journal.pone.0278471