A minimum information standard for reproducing bench-scale bacterial cell growth and productivity

Ariel Hecht; James Filliben; Sarah A Munro; Marc Salit

doi:10.1038/s42003-018-0220-6

A minimum information standard for reproducing bench-scale bacterial cell growth and productivity

Commun Biol. 2018 Dec 6:1:219. doi: 10.1038/s42003-018-0220-6. eCollection 2018.

Authors

Ariel Hecht^{1

2

3}, James Filliben⁴, Sarah A Munro^{1

2

3

5}, Marc Salit^{1

2

3

6}

Affiliations

¹ Joint Initiative for Metrology in Biology, 443 Via Ortega, Room 325, Stanford, CA 94305 USA.
² 2Genome-scale Measurements Group, National Institute of Standards and Technology, 443 Via Ortega, Room 325, Stanford, CA 94305 USA.
³ 3Department of Bioengineering, Stanford University, 443 Via Ortega, Room 325, Stanford, CA 94035 USA.
⁴ 4Statistical Engineering Division, 100 Bureau Drive, National Institute of Standards and Technology, Gaithersburg, MD 20899 USA.
⁵ 6Present Address: Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, Minnesota, 55455 USA.
⁶ 5SLAC National Accelerator Laboratory, Menlo Park, CA 94025 USA.

Abstract

Reproducing, exchanging, comparing, and building on each other's work is foundational to technological advances. Advancing biotechnology calls for reliable reuse of engineered organisms. Reliable reuse of engineered organisms requires reproducible growth and productivity. Here, we identify the experimental factors that have the greatest effect on the growth and productivity of our engineered organisms in order to demonstrate reproducibility for biotechnology. We present a draft of a Minimum Information Standard for Engineered Organism Experiments (MIEO) based on this method. We evaluate the effect of 22 factors on Escherichia coli engineered to produce the small molecule lycopene, and 18 factors on E. coli engineered to produce red fluorescent protein. Container geometry and shaking have the greatest effect on product titer and yield. We reproduce our results under two different conditions of reproducibility: conditions of use (different fractional factorial experiments), and time (48 biological replicates performed on 12 different days over 4 months).