An optimized methanol assimilation pathway relying on promiscuous formaldehyde-condensing aldolases in E. coli

Engineering biotechnological microorganisms to use methanol as a feedstock for bioproduction is a major goal for the synthetic metabolism community. Here, we aim to redesign the natural serine cycle for implementation in E. coli. We propose the homoserine cycle, relying on two promiscuous formaldehyde aldolase reactions, as a superior pathway design. The homoserine cycle is expected to outperform the serine cycle and its variants with respect to biomass yield, thermodynamic favorability, and integration with host endogenous metabolism. Even as compared to the RuMP cycle, the most efficient naturally occurring methanol assimilation route, the homoserine cycle is expected to support higher yields of a wide array of products. We test the in vivo feasibility of the homoserine cycle by constructing several E. coli gene deletion strains whose growth is coupled to the activity of different pathway segments. Using this approach, we demonstrate that all required promiscuous enzymes are active enough to enable growth of the auxotrophic strains. Our findings thus identify a novel metabolic solution that opens the way to an optimized methylotrophic platform.

Research Note: The effect of selection for 16-week body weight on turkey serum metabolome

The phenotype of modern commercial turkeys is substantially different than that of unselected, heritage turkey lines. These phenotypic changes have arisen from alterations in the genome/transcriptome, as well as the influence of many external factors on growth performance including nutrition, environment, and management. To investigate the phenotypic changes resulting from genetic selection for increased body weight, The Ohio State University maintains 2 unique genetic turkey lines: the randombred control (RBC2) line, which is comprised of genetics from 1960 era commercial turkeys and has been maintained without conscious selection for any trait; and the F line, which was originally selected from the RBC2 line and has been selected for increased 16 wk body weight for over 50 generations. This study used broad-spectrum mass-spectrometry profiling techniques to identify and quantify differences in the metabolome of the serum of F and RBC2 turkey lines. Serum samples from both F and RBC2 turkeys were subject to quantitative time of flight liquid chromatography tandem mass spectrometry analyses. Principle component analyses showed distinct populations of metabolites in the F vs. RBC2 serum, suggesting that increased body weight is associated with the accumulation of several metabolites. Comparing the spectral features to online databases resulted in the selection of 104 features with potentially identifiable chemical structures. Of these 104 features, 25 were found at higher levels in the serum of the RBC2 line turkeys, while 79 were found at a greater abundance in the F line turkeys. A more detailed analysis of these 104 features allowed for the putative identification of 49 compounds, which were clustered into 6 functional groups: 1) energy metabolism; 2) vitamins; 3) hormones and signaling molecules; 4) lipid derivatives, fatty acid metabolites, and membrane components; 5) amino acid/protein metabolism; and 6) microbial metabolites. Further validation and experimentation is needed to confirm the identity of these metabolites and understand their biological relevance and association with selection for increased body weight.

Design and engineering of E. coli metabolic sensor strains with a wide sensitivity range for glycerate

Microbial biosensors are used to detect the presence of compounds provided externally or produced internally. The latter case is commonly constrained by the need to screen a large library of enzyme or pathway variants to identify those that can efficiently generate the desired compound. To address this limitation, we suggest the use of metabolic sensor strains which can grow only if the relevant compound is present and thus replace screening with direct selection. We used a computational platform to design metabolic sensor strains with varying dependencies on a specific compound. Our method systematically explores combinations of gene deletions and identifies how the growth requirement for a compound changes with the media composition. We demonstrate this approach by constructing a set of E. coli glycerate sensor strains. In each of these strains a different set of enzymes is disrupted such that central metabolism is effectively dissected into multiple segments, each requiring a dedicated carbon source. We find an almost perfect match between the predicted and experimental dependence on glycerate and show that the strains can be used to accurately detect glycerate concentrations across two orders of magnitude. Apart from demonstrating the potential application of metabolic sensor strains, our work reveals key phenomena in central metabolism, including spontaneous degradation of central metabolites and the importance of metabolic sinks for balancing small metabolic networks.

Continuous crossbreeding of sake yeasts using growth selection systems for a-type and α-type cells

Sake yeasts belong to the budding yeast species Saccharomyces cerevisiae and have high fermentation activity and ethanol production. Although the traditional crossbreeding of sake yeasts is a time-consuming and inefficient process due to the low sporulation rates and spore viability of these strains, considerable effort has been devoted to the development of hybrid strains with superior brewing characteristics. In the present work, we describe a growth selection system for a- and α-type cells aimed at the crossbreeding of industrial yeasts, and performed hybridizations with sake yeast strains Kyokai No. 6, No. 7 and No. 9 to examine the feasibility of this approach. We successfully generated both a- and α-type strains from all parental strains, and acquired six types of hybrids by outcrossing. One of these hybrid strains was subjected to continuous crossbreeding, yielding the multi-hybrid strain, which inherited the genetic characteristics of Kyokai No. 6, No. 7 and No. 9. Notably, because all of the genetic modifications of the yeast cells were introduced using plasmids, these traits can be easily removed. The approach described here has the potential to markedly accelerate the crossbreeding of industrial yeast strains with desirable properties.