Yeast knockout library allows for efficient testing of genomic mutations for cell-free protein synthesis

Engineering cell-free systems by chemoproteomic-assisted phenotypic screening

Phenotypic screening is a valuable tool to both understand and engineer complex biological systems. We demonstrate the functionality of this approach in the development of cell-free protein synthesis (CFPS) technology. Phenotypic screening identified numerous compounds that enhanced protein production in yeast lysate CFPS reactions. Notably, many of these were competitive ATP kinase inhibitors, with the exploitation of their inherent substrate promiscuity redirecting ATP flux towards heterologous protein expression. Chemoproteomic-guided strain engineering partially phenocopied drug effects, with a 30% increase in protein yield observed upon deletion of the ATP-consuming SSA1 component of the HSP70 chaperone. Moreover, drug-mediated metabolic rewiring coupled with template optimization generated the highest protein yields in yeast CFPS to date using a hitherto less efficient, but more cost-effective glucose energy regeneration system. Our approach highlights the utility of target-agnostic phenotypic screening and target identification to deconvolute cell-lysate complexity, adding to the expanding repertoire of strategies for improving CFPS.

Amino acid balancing for the prediction and evaluation of protein concentrations in cell-free protein synthesis systems

Cell-free protein synthesis (CFPS) systems are an attractive method to complement the usual cell-based synthesis of proteins, especially for screening approaches. The literature describes a wide variety of CFPS systems, but their performance is difficult to compare since the reaction components are often used at different concentrations. Therefore, we have developed a calculation tool based on amino acid balancing to evaluate the performance of CFPS by determining the fractional yield as the ratio between theoretically achievable and experimentally achieved protein molar concentration. This tool was applied to a series of experiments from our lab and to various systems described in the literature to identify systems that synthesize proteins very efficiently and those that still have potential for higher yields. The well-established Escherichia coli system showed a high efficiency in the utilization of amino acids, but interestingly, less considered systems, such as those based on Vibrio natriegens or Leishmania tarentolae, also showed exceptional fractional yields of over 70% and 90%, respectively, implying very efficient conversions of amino acids. The methods and tools described here can quickly identify when a system has reached its maximum or has limitations. We believe that this approach will facilitate the evaluation and optimization of existing CFPS systems and provides the basis for the systematic development of new CFPS systems.

Research progress on the application of cell-free synthesis systems for enzymatic processes

Cell-free synthesis systems can complete the transcription and translation process in vitro to produce complex proteins that are difficult to be expressed in traditional cell-based systems. Such systems also can be used for the assembly of efficient localized multienzyme cascades to synthesize products that are toxic to cells. Cell-free synthesis systems provide a simpler and faster engineering solution than living cells, allowing unprecedented design freedom. This paper reviews the latest progress on the application of cell-free synthesis systems in the field of enzymatic catalysis, including cell-free protein synthesis and cell-free metabolic engineering. In cell-free protein synthesis: complex proteins, toxic proteins, membrane proteins, and artificial proteins containing non-natural amino acids can be easily synthesized by directly controlling the reaction conditions in the cell-free system. In cell-free metabolic engineering, the synthesis of desired products can be made more specific and efficient by designing metabolic pathways and screening biocatalysts based on purified enzymes or crude extracts. Through the combination of cell-free synthesis systems and emerging technologies, such as: synthetic biology, microfluidic control, cofactor regeneration, and artificial scaffolds, we will be able to build increasingly complex biomolecule systems. In the next few years, these technologies are expected to mature and reach industrialization, providing innovative platforms for a wide range of biotechnological applications.

An integrated in vivo/in vitro framework to enhance cell-free biosynthesis with metabolically rewired yeast extracts

Cell-free systems using crude cell extracts present appealing opportunities for designing biosynthetic pathways and enabling sustainable chemical synthesis. However, the lack of tools to effectively manipulate the underlying host metabolism in vitro limits the potential of these systems. Here, we create an integrated framework to address this gap that leverages cell extracts from host strains genetically rewired by multiplexed CRISPR-dCas9 modulation and other metabolic engineering techniques. As a model, we explore conversion of glucose to 2,3-butanediol in extracts from flux-enhanced Saccharomyces cerevisiae strains. We show that cellular flux rewiring in several strains of S. cerevisiae combined with systematic optimization of the cell-free reaction environment significantly increases 2,3-butanediol titers and volumetric productivities, reaching productivities greater than 0.9 g/L-h. We then show the generalizability of the framework by improving cell-free itaconic acid and glycerol biosynthesis. Our coupled in vivo/in vitro metabolic engineering approach opens opportunities for synthetic biology prototyping efforts and cell-free biomanufacturing.

Setting Up an Automated Biomanufacturing Laboratory

Laboratory automation is a key enabling technology for genetic engineering that can lead to higher throughput, more efficient and accurate experiments, better data management and analysis, decrease in the DBT (Design, Build, and Test) cycle turnaround, increase of reproducibility, and savings in lab resources. Choosing the correct framework among so many options available in terms of software, hardware, and skills needed to operate them is crucial for the success of any automation project. This chapter explores the multiple aspects to be considered for the solid development of a biofoundry project including available software and hardware tools, resources, strategies, partnerships, and collaborations in the field needed to speed up the translation of research results to solve important society problems.

Holistic engineering of cell-free systems through proteome-reprogramming synthetic circuits

Synthetic biology has focused on engineering genetic modules that operate orthogonally from the host cells. A synthetic biological module, however, can be designed to reprogram the host proteome, which in turn enhances the function of the synthetic module. Here, we apply this holistic synthetic biology concept to the engineering of cell-free systems by exploiting the crosstalk between metabolic networks in cells, leading to a protein environment more favorable for protein synthesis. Specifically, we show that local modules expressing translation machinery can reprogram the bacterial proteome, changing the expression levels of more than 700 proteins. The resultant feedback generates a cell-free system that can synthesize fluorescent reporters, protein nanocages, and the gene-editing nuclease Cas9, with up to 5-fold higher expression level than classical cell-free systems. Our work demonstrates a holistic approach that integrates synthetic and systems biology concepts to achieve outcomes not possible by only local, orthogonal circuits.

A PEGDA/DNA Hybrid Hydrogel for Cell-Free Protein Synthesis

Cell-free protein synthesis (CFPS) has the advantage of rapid expression of proteins and has been widely implemented in synthetic biology and protein engineering. However, the critical problem limiting CFPS industrial application is its relatively high cost, which partly attributes to the overexpense of single-use DNA templates. Hydrogels provide a possible solution because they can preserve and reutilize the DNA templates in CFPS and have great potential in elevating the protein production yield of the CFPS. Here, we presented a low-cost hybrid hydrogel simply prepared with polyethylene glycol diacrylate (PEGDA) and DNA, which is capable of high-efficient and repeated protein synthesis in CFPS. Parameters governing protein production specific to hybrid hydrogels were optimized. Structures and physical properties of the hybrid hydrogel were characterized. Transcription and expression kinetics of solution phase system and gel phased systems were investigated. The results showed that PEGDA/DNA hydrogel can enhance the protein expression of the CFPS system and enable a repeated protein production for tens of times. This PEGDA/DNA hybrid hydrogel can serve as a recyclable gene carrier for either batch or continuous protein expression, and paves a path toward more powerful, scalable protein production and cell-free synthetic biology.

Coronary Angiography for Follow-up of Heart Transplant Recipients: Usefulness of the Gensini Score

OBJECTIVES

Posttransplant cardiac allograft vasculo-pathy affects long-term survival after heart transplant. Because cardiac transplant recipients do not feel angina pectoris as a result of denervation of the transplanted heart graft, early diagnosis is difficult. The Gensini score, a widely used and simple scoring system, can determine the severity of coronary artery disease by angiography. Although this system has been widely used to evaluate natural coronary atherosclerosis, its use in heart transplant recipients has not been studied. Here, we evaluated cardiac allograft vasculo-pathy using the Gensini score.

MATERIALS AND METHODS

We retrospectively analyzed 105 heart transplant patients seen between February 2004 and April 2018, including their immunosuppressive therapies. The Gensini score was calculated to determine severity score for each coronary stenosis according to degree of luminal narrowing and location.

RESULTS

Of 105 heart transplant patients, 21 were diagnosed with cardiac allograft vasculopathy. Most patients received tacrolimus, prednisolone, and mycophenolate mofetil as standard therapy. Of 63 included patients, 21 (33.3%) showed cardiac allograft vasculopathy on coronary angiography. In accordance with the International Society of Heart and Lung Transplantation rating system, 42 of 63 patients (66.6%) were rated as 0 (no detectable angiographic lesions). Mean Gensini score was 34.8 ± 26. In the 21 patients with cardiac allograft vasculopathy, Gensini score showed mild cardiac allograft vas-culopathy (score ≤ 10) in 8 patients (38%), moderate (score > 10 and ≤ 40) in 6 patients (28.5%), and severe (score > 40) in 7 patients (33.3%). Angiographic coronary artery disease burden using Gensini was strongly correlated with cardiac allograft vasculopathy severity.

CONCLUSIONS

The Gensini score could provide valid assessment of cardiac allograft vasculopathy burden for use in clinical practice. However, more research is needed to identify and treat cardiac allograft vasculopathy for successful long-term survival of heart transplant patients.

Development of a Pseudomonas putida cell-free protein synthesis platform for rapid screening of gene regulatory elements

Cell-free protein synthesis (CFPS) systems enable the production of protein without the use of living, intact cells. An emerging area of interest is to use CFPS systems to characterize individual elements for genetic programs [e.g. promoters, ribosome binding sites (RBS)]. To enable this research area, robust CFPS systems must be developed from new chassis organisms. One such chassis is the Gram-negative Pseudomonas bacteria, which have been studied extensively for their diverse metabolism with promises in the field of bioremediation and biosynthesis. Here, we report the development and optimization of a high-yielding (198 ± 5.9 µg/ml) batch CFPS system from Pseudomonas putida ATCC 12633. Importantly, both circular and linear DNA templates can be applied directly to the CFPS reaction to program protein synthesis. Therefore, it is possible to prepare hundreds or even thousands of DNA templates without time-consuming cloning work. This opens the possibility to rapidly assess and validate genetic part performance in vitro before performing experiments in cells. To validate the P. putida CFPS system as a platform for prototyping genetic parts, we designed and constructed a library consisting of 15 different RBSs upstream of the reporter protein sfGFP, which covered an order of magnitude range in expression. Looking forward, our P. putida CFPS platform will not only expand the protein synthesis toolkit for synthetic biology but also serve as a platform in expediting the screening and prototyping of gene regulatory elements.

Metabolomic Studies of Indonesian Jamu Medicines: Prediction of Jamu Efficacy and Identification of Important Metabolites

In order to obtain a better understanding why some Jamu formulas can be used to treat a specific disease, we performed metabolomic studies of Jamu by taking into consideration the biologically active compounds existing in plants used as Jamu ingredients. A thorough integration of information from omics is expected to provide solid evidence-based scientific rationales for the development of modern phytomedicines. This study focused on prediction of Jamu efficacy based on its component metabolites and also identification of important metabolites related to each efficacy group. Initially, we compared the performance of Support Vector Machines and Random Forest to predict the Jamu efficacy with three different data pre-processing approaches, such as no filtering, Single Filtering algorithm, and a combination of Single Filtering algorithm and feature selection using Regularized Random Forest. Both classifiers performed very well and according to 5-fold cross-validation results, the mean accuracy of Support Vector Machine with linear kernel was slightly better than Random Forest. It can be concluded that machine learning methods can successfully relate Jamu efficacy with metabolites. In addition, we extended our analysis by identifying important metabolites from the Random Forest model. The inTrees framework was used to extract the rules and to select important metabolites for each efficacy group. Overall, we identified 94 significant metabolites associated to 12 efficacy groups and many of them were validated by published literature and KNApSAcK Metabolite Activity database.

Cell-Free Mixing of Escherichia coli Crude Extracts to Prototype and Rationally Engineer High-Titer Mevalonate Synthesis

Cell-free metabolic engineering (CFME) is advancing a powerful paradigm for accelerating the design and synthesis of biosynthetic pathways. However, as most cell-free biomolecule synthesis systems to date use purified enzymes, energy and cofactor balance can be limiting. To address this challenge, we report a new CFME framework for building biosynthetic pathways by mixing multiple crude lysates, or extracts. In our modular approach, cell-free lysates, each selectively enriched with an overexpressed enzyme, are generated in parallel and then combinatorically mixed to construct a full biosynthetic pathway. Endogenous enzymes in the cell-free extract fuel high-level energy and cofactor regeneration. As a model, we apply our framework to synthesize mevalonate, an intermediate in isoprenoid synthesis. We use our approach to rapidly screen enzyme variants, optimize enzyme ratios, and explore cofactor landscapes for improving pathway performance. Further, we show that genomic deletions in the source strain redirect metabolic flux in resultant lysates. In an optimized system, mevalonate was synthesized at 17.6 g·L^-1 (119 mM) over 20 h, resulting in a volumetric productivity of 0.88 g·L^-1·hr^-1. We also demonstrate that this system can be lyophilized and retain biosynthesis capability. Our system catalyzes ∼1250 turnover events for the cofactor NAD⁺ and demonstrates the ability to rapidly prototype and debug enzymatic pathways in vitro for compelling metabolic engineering and synthetic biology applications.