Jay D. Keasling

Selecting RNA aptamers for synthetic biology: investigating magnesium dependence and predicting binding affinity

The ability to generate RNA aptamers for synthetic biology using in vitro selection depends on the informational complexity (IC) needed to specify functional structures that bind target ligands with desired affinities in physiological concentrations of magnesium. We investigate how selection for high-affinity aptamers is constrained by chemical properties of the ligand and the need to bind in low magnesium. We select two sets of RNA aptamers that bind planar ligands with dissociation constants (Kds) ranging from 65 nM to 100 μM in physiological buffer conditions. Aptamers selected to bind the non-proteinogenic amino acid, p-amino phenylalanine (pAF), are larger and more informationally complex (i.e., rarer in a pool of random sequences) than aptamers selected to bind a larger fluorescent dye, tetramethylrhodamine (TMR). Interestingly, tighter binding aptamers show less dependence on magnesium than weaker-binding aptamers. Thus, selection for high-affinity binding may automatically lead to structures that are functional in physiological conditions (1–2.5 mM Mg2+). We hypothesize that selection for high-affinity binding in physiological conditions is primarily constrained by ligand characteristics such as molecular weight (MW) and the number of rotatable bonds. We suggest that it may be possible to estimate aptamer–ligand affinities and predict whether a particular aptamer-based design goal is achievable before performing the selection.

Synthetic and systems biology for microbial production of commodity chemicals

The combination of synthetic and systems biology is a powerful framework to study fundamental questions in biology and produce chemicals of immediate practical application such as biofuels, polymers, or therapeutics. However, we cannot yet engineer biological systems as easily and precisely as we engineer physical systems. In this review, we describe the path from the choice of target molecule to scaling production up to commercial volumes. We present and explain some of the current challenges and gaps in our knowledge that must be overcome in order to bring our bioengineering capabilities to the level of other engineering disciplines. Challenges start at molecule selection, where a difficult balance between economic potential and biological feasibility must be struck. Pathway design and construction have recently been revolutionized by next-generation sequencing and exponentially improving DNA synthesis capabilities. Although pathway optimization can be significantly aided by enzyme expression characterization through proteomics, choosing optimal relative protein expression levels for maximum production is still the subject of heuristic, non-systematic approaches. Toxic metabolic intermediates and proteins can significantly affect production, and dynamic pathway regulation emerges as a powerful but yet immature tool to prevent it. Host engineering arises as a much needed complement to pathway engineering for high bioproduct yields; and systems biology approaches such as stoichiometric modeling or growth coupling strategies are required. A final, and often underestimated, challenge is the successful scale up of processes to commercial volumes. Sustained efforts in improving reproducibility and predictability are needed for further development of bioengineering.

Engineering glucose metabolism of Escherichia coli under nitrogen starvation

A major aspect of microbial metabolic engineering is the development of chassis hosts that have favorable global metabolic phenotypes, and can be further engineered to produce a variety of compounds. In this work, we focus on the problem of decoupling growth and production in the model bacterium Escherichia coli, and in particular on the maintenance of active metabolism during nitrogen-limited stationary phase. We find that by overexpressing the enzyme PtsI, a component of the glucose uptake system that is inhibited by α-ketoglutarate during nitrogen limitation, we are able to achieve a fourfold increase in metabolic rates. Alternative systems were also tested: chimeric PtsI proteins hypothesized to be insensitive to α-ketoglutarate did not improve metabolic rates under the conditions tested, whereas systems based on the galactose permease GalP suffered from energy stress and extreme sensitivity to expression level. Overexpression of PtsI is likely to be a useful arrow in the metabolic engineer’s quiver as productivity of engineered pathways becomes limited by central metabolic rates during stationary phase production processes.

Guiding optimal biofuels

In the current study, processes to produce either ethanol or a representative fatty acid ethyl ester (FAEE) via the fermentation of sugars liberated from lignocellulosic materials pretreated in acid or alkaline environments are analyzed in terms of economic and environmental metrics. Simplified process models are introduced and employed to estimate process performance, and Monte Carlo analyses were carried out to identify key sources of uncertainty and variability. We find that the near-term performance of processes to produce FAEE is significantly worse than that of ethanol production processes for all metrics considered, primarily due to poor fermentation yields and higher electricity demands for aerobic fermentation. In the longer term, the reduced cost and energy requirements of FAEE separation processes will be at least partially offset by inherent limitations in the relevant metabolic pathways that constrain the maximum yield potential of FAEE from biomass-derived sugars.