Automation assisted anaerobic phenotyping for metabolic engineering.

BACKGROUND: Microorganisms can be metabolically engineered to produce a wide range of commercially important chemicals. Advancements in computational strategies for strain design and synthetic biological techniques to construct the designed strains have facilitated the generation of large libraries of potential candidates for chemical production. Consequently, there is a need for high-throughput laboratory scale techniques to characterize and screen these candidates to select strains for further investigation in large scale fermentation processes. Several small-scale fermentation techniques, in conjunction with laboratory automation have enhanced the throughput of enzyme and strain phenotyping experiments. However, such high throughput experimentation typically entails large operational costs and generate massive amounts of laboratory plastic waste. RESULTS: In this work, we develop an eco-friendly automation workflow that effectively calibrates and decontaminates fixed-tip liquid handling systems to reduce tip waste. We also investigate inexpensive methods to establish anaerobic conditions in microplates for high-throughput anaerobic phenotyping. To validate our phenotyping platform, we perform two case studies-an anaerobic enzyme screen, and a microbial phenotypic screen. We used our automation platform to investigate conditions under which several strains of E. coli exhibit the same phenotypes in 0.5 L bioreactors and in our scaled-down fermentation platform. We also propose the use of dimensionality reduction through t-distributed stochastic neighbours embedding (t-SNE) in conjunction with our phenotyping platform to effectively cluster similarly performing strains at the bioreactor scale. CONCLUSIONS: Fixed-tip liquid handling systems can significantly reduce the amount of plastic waste generated in biological laboratories and our decontamination and calibration protocols could facilitate the widespread adoption of such systems. Further, the use of t-SNE in conjunction with our automation platform could serve as an effective scale-down model for bioreactor fermentations. Finally, by integrating an in-house data-analysis pipeline, we were able to accelerate the 'test' phase of the design-build-test-learn cycle of metabolic engineering.

Wireless bioreactor for anaerobic cultivation of bacteria.

Anaerobic cultivation methods of bacteria are indispensable in microbiology. One methodology is to cultivate the microbes in anaerobic enclosure with oxygen-adosrbing chemicals. Here, we report an electronic extension of such strategy for facultative anaerobic bacteria. The technique is based a bioreactor with entire operation including turbidity measurement, fluidic mixing, and gas delivery in an anaerobic enclosure. Wireless data transmission is employed and the anaerobic condition is achieved with gas pack. Although the technique is not meant to completely replace the anaerobic chamber for strict anaerobic bacteria, it provides a convenient way to bypass the cumbersome operation in anaerobic chamber for facultative anaerobic bacteria. Such a cultivation strategy is demonstrated with Escherichia coli with different carbon sources and hydrogen as energy source.

Structural nanotechnology: three-dimensional cryo-EM and its use in the development of nanoplatforms for in vitro catalysis.

The organization of enzymes into different subcellular compartments is essential for correct cell function. Protein-based cages are a relatively recently discovered subclass of structurally dynamic cellular compartments that can be mimicked in the laboratory to encapsulate enzymes. These synthetic structures can then be used to improve our understanding of natural protein-based cages, or as nanoreactors in industrial catalysis, metabolic engineering, and medicine. Since the function of natural protein-based cages is related to their three-dimensional structure, it is important to determine this at the highest possible resolution if viable nanoreactors are to be engineered. Cryo-electron microscopy (cryo-EM) is ideal for undertaking such analyses within a feasible time frame and at near-native conditions. This review describes how three-dimensional cryo-EM is used in this field and discusses its advantages. An overview is also given of the nanoreactors produced so far, their structure, function, and applications.

Liquid Chromatography and Mass Spectrometry Analysis of Isoprenoid Intermediates in Escherichia coli.

Isoprenoids are a highly diverse group of natural products with broad application as high value chemicals and advanced biofuels. They are synthesized using two primary building blocks, namely, isopentenyl diphosphate (IPP) and dimethylallyl diphosphate (DMAPP) that are generated via the mevalonate (MVA) or deoxy-D-xylulose-5-phosphate (DXP) pathways. Isoprenoid biosynthetic pathways are prevalent in eukaryotes, archaea, and bacteria. Measurement of isoprenoid intermediates via standard liquid chromatography-mass spectrometry (LC-MS) protocols is generally challenging because of the hydrophilicity and complex physicochemical properties of the molecules. In addition, there is currently no reliable analytical method that can simultaneously measure metabolic intermediates from MVA and DXP pathways, including the prenyl diphosphates. Therefore, we describe a robust hydrophilic interaction liquid chromatography time-of-flight mass spectrometry (HILIC-TOF-MS) method for analyzing isoprenoid intermediates from metabolically engineered Escherichia coli strains.

Intracellular Imaging of Protein-Specific Glycosylation.

Posttranslational protein glycosylation is conserved in all kingdoms of life and implicated in the regulation of protein structure, function, and localization. The visualization of glycosylation states of designated proteins within living cells is of great importance for unraveling the biological roles of intracellular protein glycosylation. Our generally applicable approach is based on the incorporation of a glucosamine analog, Ac4GlcNCyoc, into the cellular glycome via metabolic engineering. Ac4GlcNCyoc can be labeled in a second step via inverse-electron-demand Diels-Alder chemistry with fluorophores inside living cells. Additionally, target proteins can be expressed as enhanced green fluorescent protein (EGFP)-fusion proteins. To assess the proximity of the donor EGFP and the glycan-anchored acceptor fluorophore, Förster resonance energy transfer (FRET) is employed and read out with high contrast by fluorescence lifetime imaging (FLIM) microscopy. In this chapter, we present a detailed description of methods required to perform protein-specific imaging of glycosylation inside living cells. These include the complete synthesis of Ac4GlcNCyoc, immunoprecipitation of EGFP-fusion proteins to examine the Ac4GlcNCyoc modification state, and a complete section on basics, performance, as well as data analysis for FLIM-FRET microscopy. We also provide useful notes necessary for reproducibility and point out strengths and limitations of the approach.

Customized microscale approach for optimizing two-phase bio-oxidations of alkanes with high reproducibility.

BACKGROUND: Numerous challenges remain to achieve industrially competitive space-time yields for bio-oxidations. The ability to rapidly screen bioconversion reactions for characterization and optimization is of major importance in bioprocess development and biocatalyst selection; studies at conventional lab scale are time consuming and labor intensive with low experimental throughput. The direct ω-oxyfunctionalization of aliphatic alkanes in a regio- and chemoselective manner is efficiently catalyzed by monooxygenases such as the AlkBGT enzyme complex from Pseudomonas putida under mild conditions. However, the adoption of microscale tools for these highly volatile substrates has been hindered by excessive evaporation and material incompatibility. RESULTS: This study developed and validated a robust high-throughput microwell platform for whole-cell two-liquid phase bio-oxidations of highly volatile n-alkanes. Using microwell plates machined from polytetrafluoroethylene and a sealing clamp, highly reproducible results were achieved with no significant variability such as edge effects determined. A design of experiment approach using a response surface methodology was adopted to systematically characterize the system and identify non-limiting conditions for a whole cell bioconversion of dodecane. Using resting E. coli cells to control cell concentration and reducing the fill volume it is possible to operate in non-limiting conditions with respect to oxygen and glucose whilst achieving relevant total product yields (combining 1-dodecanol, dodecanal and dodecanoic acid) of up to 1.5 mmol g DCW-1 . CONCLUSIONS: Overall, the developed microwell plate greatly improves experimental throughput, accelerating the screening procedures specifically for biocatalytic processes in non-conventional media. Its simplicity, robustness and standardization ensure high reliability of results.

Microfluidics and microbial engineering.

The combination of microbial engineering and microfluidics is synergistic in nature. For example, microfluidics is benefiting from the outcome of microbial engineering and many reported point-of-care microfluidic devices employ engineered microbes as functional parts for the microsystems. In addition, microbial engineering is facilitated by various microfluidic techniques, due to their inherent strength in high-throughput screening and miniaturization. In this review article, we firstly examine the applications of engineered microbes for toxicity detection, biosensing, and motion generation in microfluidic platforms. Secondly, we look into how microfluidic technologies facilitate the upstream and downstream processes of microbial engineering, including DNA recombination, transformation, target microbe selection, mutant characterization, and microbial function analysis. Thirdly, we highlight an emerging concept in microbial engineering, namely, microbial consortium engineering, where the behavior of a multicultural microbial community rather than that of a single cell/species is delineated. Integrating the disciplines of microfluidics and microbial engineering opens up many new opportunities, for example in diagnostics, engineering of microbial motors, development of portable devices for genetics, high throughput characterization of genetic mutants, isolation and identification of rare/unculturable microbial species, single-cell analysis with high spatio-temporal resolution, and exploration of natural microbial communities.

MESSI: metabolic engineering target selection and best strain identification tool.

Metabolic engineering and synthetic biology are synergistically related fields for manipulating target pathways and designing microorganisms that can act as chemical factories. Saccharomyces cerevisiae's ideal bioprocessing traits make yeast a very attractive chemical factory for production of fuels, pharmaceuticals, nutraceuticals as well as a wide range of chemicals. However, future attempts of engineering S. cerevisiae's metabolism using synthetic biology need to move towards more integrative models that incorporate the high connectivity of metabolic pathways and regulatory processes and the interactions in genetic elements across those pathways and processes. To contribute in this direction, we have developed Metabolic Engineering target Selection and best Strain Identification tool (MESSI), a web server for predicting efficient chassis and regulatory components for yeast bio-based production. The server provides an integrative platform for users to analyse ready-to-use public high-throughput metabolomic data, which are transformed to metabolic pathway activities for identifying the most efficient S. cerevisiae strain for the production of a compound of interest. As input MESSI accepts metabolite KEGG IDs or pathway names. MESSI outputs a ranked list of S. cerevisiae strains based on aggregation algorithms. Furthermore, through a genome-wide association study of the metabolic pathway activities with the strains' natural variation, MESSI prioritizes genes and small variants as potential regulatory points and promising metabolic engineering targets. Users can choose various parameters in the whole process such as (i) weight and expectation of each metabolic pathway activity in the final ranking of the strains, (ii) Weighted AddScore Fuse or Weighted Borda Fuse aggregation algorithm, (iii) type of variants to be included, (iv) variant sets in different biological levels.Database URL: http://sbb.hku.hk/MESSI/.

Development of biosensors and their application in metabolic engineering.

In a sustainable bioeconomy, many commodities and high value chemicals, including pharmaceuticals, will be manufactured using microbial cell factories from renewable feedstocks. These cell factories can be efficiently generated by constructing libraries of diversified genomes followed by screening for the desired phenotypes. However, methods available for microbial genome diversification far exceed our ability to screen and select for those variants with optimal performance. Genetically encoded biosensors have shown the potential to address this gap, given their ability to respond to small molecule binding and ease of implementation with high-throughput analysis. Here we describe recent progress in biosensor development and their applications in a metabolic engineering context. We also highlight examples of how biosensors can be integrated with synthetic circuits to exert feedback regulation on the metabolism for improved performance of cell factories.

Evaluation of exogenous siRNA addition as a metabolic engineering tool for modifying biopharmaceuticals.

Traditional metabolic engineering approaches, including homologous recombination, zinc-finger nucleases, and short hairpin RNA, have previously been used to generate biologics with specific characteristics that improve efficacy, potency, and safety. An alternative approach is to exogenously add soluble small interfering RNA (siRNA) duplexes, formulated with a cationic lipid, directly to cells grown in shake flasks or bioreactors. This approach has the following potential advantages: no cell line development required, ability to tailor mRNA silencing by adjusting siRNA concentration, simultaneous silencing of multiple target genes, and potential temporal control of down regulation of target gene expression. In this study, we demonstrate proof of concept of the siRNA feeding approach as a metabolic engineering tool in the context of increasing monoclonal antibody (MAb) afucosylation. First, potent siRNA duplexes targeting fut8 and gmds were dosed into shake flasks with cells that express an anti-CD20 MAb. Dose response studies demonstrated the ability to titrate the silencing effect. Furthermore, siRNA addition resulted in no deleterious effects on cell growth, final protein titer, or specific productivity. In bioreactors, antibodies produced by cells following siRNA treatment exhibited improved functional characteristics compared to antibodies from untreated cells, including increased levels of afucosylation (63%), a 17-fold improvement in FCgRIIIa binding, and an increase in specific cell lysis by up to 30%, as determined in an Antibody-Dependent Cellular Cytoxicity (ADCC) assay. In addition, standard purification procedures effectively cleared the exogenously added siRNA and transfection agent. Moreover, no differences were observed when other key product quality structural attributes were compared to untreated controls. These results establish that exogenous addition of siRNA represents a potentially novel metabolic engineering tool to improve biopharmaceutical function and quality that can complement existing metabolic engineering methods.

Rapid strain evaluation using dynamic DO-stat fed-batch fermentation under scale-down conditions.

While large amount of strains can be quickly generated via metabolic engineering, the speed/efficiency of evaluating each strain becomes the bottleneck in the process from strain development to final production. In this chapter, a method is introduced to rapidly evaluate strain performance in fed-batch fermentation mode by using dynamic dissolved oxygen stat feed back control with no additional advanced online measurement. In addition, a scale-down feature is integrated in the method to mimic the limitation of oxygen transfer in large-scale vessels, so that strains can be evaluated under the conditions close to that in large-scale bioreactors. The method has been implemented in several commercial standard benchtop scale fermentation systems with different fermentation control software.