Lessons from Two Design–Build–Test–Learn Cycles of Dodecanol Production in Escherichia coli Aided by Machine Learning

The Design–Build–Test–Learn (DBTL) cycle, facilitated by exponentially improving capabilities in synthetic biology, is an increasingly adopted metabolic engineering framework that represents a more systematic and efficient approach to strain development than historical efforts in biofuels and biobased products. Here, we report on implementation of two DBTL cycles to optimize 1-dodecanol production from glucose using 60 engineered Escherichia coli MG1655 strains. The first DBTL cycle employed a simple strategy to learn efficiently from a relatively small number of strains (36), wherein only the choice of ribosome-binding sites and an acyl-ACP/acyl-CoA reductase were modulated in a single pathway operon including genes encoding a thioesterase (UcFatB1), an acyl-ACP/acyl-CoA reductase (Maqu_2507, Maqu_2220, or Acr1), and an acyl-CoA synthetase (FadD). Measured variables included concentrations of dodecanol and all proteins in the engineered pathway. We used the data produced in the first DBTL cycle to train several machine-learning algorithms and to suggest protein profiles for the second DBTL cycle that would increase production. These strategies resulted in a 21% increase in dodecanol titer in Cycle 2 (up to 0.83 g/L, which is more than 6-fold greater than previously reported batch values for minimal medium). Beyond specific lessons learned about optimizing dodecanol titer in E. coli, this study had findings of broader relevance across synthetic biology applications, such as the importance of sequencing checks on plasmids in production strains as well as in cloning strains, and the critical need for more accurate protein expression predictive tools

Genetic manipulation of the obligate chemolithoautotrophic bacterium Thiobacillus denitrificans

Photo shows participants at the National Gelande competitions held at Alta, Utah, in 196

Genetic manipulation of the obligate chemolithoautotrophic bacterium Thiobacillus denitrificans

Chemolithoautotrophic bacteria can be of industrial and environmental importance, but they present a challenge for systems biology studies, as their central metabolism deviates from that of model organisms and there is a much less extensive experimental basis for their gene annotation than for typical organoheterotrophs. For microbes with sequenced genomes but unconventional metabolism, the ability to create knockout mutations can be a powerful tool for functional genomics and thereby render an organism more amenable to systems biology approaches. In this chapter, we describe a genetic system for Thiobacillus denitrificans, with which insertion mutations can be introduced by homologous recombination and complemented in trans. Insertion mutations are generated by in vitro transposition, the mutated genes are amplified by the PCR, and the amplicons are introduced into T. denitrificans by electroporation. Use of a complementation vector, pTL2, based on the IncP plasmid pRR10 is also addressed

Identification of intermediates formed during anaerobic benzene degradation by an iron-reducing enrichment culture.

Anaerobic benzene degradation is an important process in contaminated aquifers but is poorly understood due to the scarcity of microbial cultures for study. We have enriched a ferric iron-reducing culture that completely mineralizes benzene to CO2. With 13C6-labelled benzene as the growth substrate, ring-labelled benzoate was identified as a major intermediate by liquid chromatography/tandem mass spectrometry (LC/MS/MS) analysis of culture supernatants. With increasing incubation time, 13C7-labelled benzoate appeared, indicating that the carboxyl group of benzoate derived from CO2 that was produced from mineralization of labelled benzene. This was confirmed by growing the culture in 13C-bicarbonate-buffered medium with unlabelled benzene as the substrate, as the label appeared in the carboxyl group of benzoate produced. Phenol was also identified as an intermediate at high concentration. However, it was clearly shown that phenol was formed abiotically by autoxidation of benzene during the sampling and analysis procedure as a result of exposure to air. The results suggest that, in our culture, anaerobic benzene degradation proceeds via carboxylation and that caution should be exercised in interpreting hydroxylated benzene derivatives as metabolic intermediates of anaerobic benzene degradation