Mass-Activated Droplet Sorting for the Selection of Lysine-Producing Escherichia coli.

Synthetic biology relies on engineering cells to have desirable properties, such as the production of select chemicals. A bottleneck in engineering methods is often the need to screen and sort variant libraries for potential activity. Droplet microfluidics is a method for high-throughput sample preparation and analysis which has the potential to improve the engineering of cells, but a limitation has been the reliance on fluorescent analysis. Here, we show the ability to select cell variants grown in 20 nL droplets at 0.5 samples/s using mass-activated droplet sorting (MADS), a method for selecting droplets based on the signal intensity measured by electrospray ionization mass spectrometry (ESI-MS). Escherichia coli variants producing lysine were used to evaluate the applicability of MADS for synthetic biology. E. coli were shown to be effectively grown in droplets, and the lysine produced by these cells was detectable using ESI-MS. Sorting of lysine-producing cells based on the MS signal was shown, yielding 96-98% purity for high-producing variants in the selected pool. Using this technique, cells were recovered after screening, enabling downstream validation via phenotyping. The presented method is translatable to whole-cell engineering for biocatalyst production.

Evaluation of Analyte Transfer between Microfluidic Droplets by Mass Spectrometry.

Droplet microfluidics enables high-throughput experimentation and screening by encapsulating chemical and biochemical samples in aqueous droplets segmented by an immiscible fluid. In such experiments, it is critical that each droplet remains chemically distinct. A common approach is to use fluorinated oils with surfactants to stabilize droplets. However, some small molecules have been observed to transport between droplets under these conditions. Attempts to study and mitigate this effect have relied on evaluating crosstalk using fluorescent molecules, which inherently limits the analyte scope and conclusions drawn about the mechanism of the effect. In this work, transport of low molecular weight compounds between droplets was investigated using electrospray ionization mass spectrometry (ESI-MS) for measurement. The use of ESI-MS significantly expands the scope of analytes that can be tested. We tested 36 structurally diverse analytes that were found to exhibit crosstalk ranging from negligible to complete transfer using HFE 7500 as the carrier fluid and 008-fluorosurfactant as a surfactant. Using this data set, we developed a predictive tool showing that high log P and log D values correlate with high crosstalk, and high polar surface area and log S correlate with low crosstalk. We then investigated several carrier fluids, surfactants, and flow conditions. It was discovered that transport is strongly dependent on all of these factors and that experimental design and surfactant tailoring can reduce carryover. We present evidence for mixed crosstalk mechanisms including both micellar and oil partitioning transfer. By understanding the driving mechanisms, surfactant and oil compositions can be designed to better reduce chemical transport for screening workflows.

High-Throughput Liquid Chromatographic Analysis Using a Segmented Flow Injector with a 1 s Cycle Time.

High-throughput screening (HTS) workflows are revolutionizing many fields, including drug discovery, reaction discovery and optimization, diagnostics, sensing, and enzyme engineering. Liquid chromatography (LC) is commonly deployed during HTS to reduce matrix effects, distinguish isomers, and preconcentrate prior to detection, but LC separation time often limits throughput. Although subsecond LC separations have been demonstrated, they are rarely utilized during HTS due to limitations associated with the speed of common autosamplers. In this work, these limits are overcome by utilizing droplet microfluidics for sample introduction. In the method, a train of samples segmented by air are continuously pumped into the inlet of an LC injection valve that is actuated once each sample fills the sample loop. Coupled with 2.1 mm diameter × 5 mm long columns packed with 2.7 µm superficially porous C18 particles operated at 5 mL/min, the injector enabled separation of 3 components at 1 s/sample and analysis of a 96-well plate in 1.6 min with <2% peak area relative standard deviation. Analyte-dependent carryover was minimized by including wash droplets composed of organic solvent in between sample droplets. High-throughput LC coupled with mass spectrometric detection using the segmented flow injector was applied to a screen of inhibitors of a cytochrome P450-catalyzed hydroxylation reaction. Measurements of the reaction substrate and product concentrations made using fast LC with the segmented flow injector correlated well with measurements made using a more conventional, 3 min LC method. These results demonstrate the potential for droplet microfluidics to be used for sample introduction during high-throughput LC analysis.

Advances in coupling droplet microfluidics to mass spectrometry.

Droplet microfluidics enables development of workflows with low sample consumption and high throughput. Fluorescence-based assays are most used with droplet microfluidics; however, the requirement of a fluorescent reporter restricts applicability of this approach. The coupling of droplets to mass spectrometry (MS) has enabled selective assays on complex mixtures to broaden the analyte scope. Droplet microfluidics has been interfaced to MS via electrospray ionization (ESI) and matrix-assisted laser desorption ionization (MALDI). The works reviewed herein outline the development of this nascent field as well as initial exploration of its application in biotechnology and bioanalysis, including synthetic biology, reaction development, and in vivo sensing.

Evaluation of three temperature- and mobile phase-dependent retention models for reversed-phase liquid chromatographic retention and apparent retention enthalpy.

Predicting retention and enthalpy allows for the simulation and optimization of advanced chromatographic techniques including gradient separations, temperature-assisted solute focusing, multidimensional liquid chromatography, and solvent focusing. In this paper we explore the fits of three expressions for retention as a function of mobile phase composition and temperature to retention data of 101 small molecules in reversed phase liquid chromatography. The three retention equations investigated are those by Neue and Kuss (NK) and two different equations by Pappa-Louisi et al., one based on a partition model (PL-P) and one based on an adsorption model (PL-A). More than 25 000 retention factors were determined for 101 small molecules under various mobile phase and temperature conditions. The pure experimental uncertainty is very small, approximately 0.22% uncertainty in retention factors measured on the same day (2.1% when performed on different days). Each of the three equations for ln(k) was fit to the experimental data based on a least-squares approach and the results were analyzed using lack-of-fit residuals. The PL-A model, while complex, gives the best overall fits. In addition to examining the equations' adequacy for retention, we also examined their use for apparent retention enthalpy. This enthalpy can be predicted by taking the derivative of these expressions with respect to the inverse of absolute temperature. The numerical values of the fitted parameters based on retention data can then be used to predict retention enthalpy. These enthalpy predictions were compared to those obtained from a modified van 't Hoff equation that included a quadratic term in inverse temperature. Based on analysis of 1 211 van 't Hoff plots (solute-mobile phase-day combinations), ninety-eight percent showed a significantly better fit when using the modified van 't Hoff expression, justifying its use to provide apparent enthalpies as a function of mobile phase composition and temperature. The foregoing apparent enthalpies were compared to the apparent enthalpies predicted by the three models. The PL-A model, which contains a temperature dependent enthalpy, provided the best enthalpy prediction. However, there is virtually no correlation between the overall lack of fit to experimental ln(k) for each model and the corresponding lack of fit of the linear (in 1/T) van 't Hoff expression. Thus, the temperature-dependent enthalpy is apparently not the cause of a model's ability to fit ln(k) as a function of mobile phase composition and temperature. The value in these expressions is their ability to predict chromatograms, allowing for optimization of an advanced chromatographic technique. The two simpler models NK and PL-P, which do not contain a temperature dependent enthalpy, have their merits in modelling retention (NK being the better of the two) and enthalpy (PL-P being the better of the two) if a simpler expression is required for a given application.