High-throughput mapping of CoA metabolites by SAMDI-MS to optimize the cell-free biosynthesis of HMG-CoA

High-resolution acoustic ejection mass spectrometry for high-throughput library screening

An approach is described for high-throughput quality assessment of drug candidate libraries using high-resolution acoustic ejection mass spectrometry (AEMS). Sample introduction from 1536-well plates is demonstrated for this application using 2.5 nL acoustically dispensed sample droplets into an Open Port Interface (OPI) with pneumatically assisted electrospray ionization at a rate of one second per sample. Both positive and negative ionization are shown to be essential to extend the compound coverage of this protease inhibitor-focused library. Specialized software for efficiently interpreting this data in 1536-well format is presented. A new high-throughput method for quantifying the concentration of the components (HTQuant) is proposed that neither requires adding an internal standard to each well nor further encumbers the high-throughput workflow. This approach for quantitation requires highly reproducible peak areas, which is shown to be consistent within 4.4 % CV for a 1536-well plate analysis. An approach for troubleshooting the workflow based on the background ion current signal is also presented. The AEMS data is compared to the industry standard LC/PDA/ELSD/MS approach and shows similar coverage but at 180-fold greater throughput. Despite the same ionization process, both methods confirmed the presence of a small percentage of compounds in wells that the other did not. The data for this relatively small, focused library is compared to a larger, more chemically diverse library to indicate that this approach can be more generally applied beyond this single case study. This capability is particularly timely considering the growing implementation of artificial intelligence strategies that require the input of large amounts of high-quality data to formulate predictions relevant to the drug discovery process. The molecular structures of the 872-compound library analyzed here are included to begin the process of correlating molecular structures with ionization efficiency and other parameters as an initial step in this direction.

Data processing for high-throughput mass spectrometry in drug discovery

INTRODUCTION

High-throughput mass spectrometry that could deliver > 10 times faster sample readout speed than traditional LC-based platforms has emerged as a powerful analytical technique, enabling the rapid analysis of complex biological samples. This increased speed of MS data acquisition has brought a critical demand for automatic data processing capabilities that should match or surpass the speed of data acquisition. Those data processing capabilities should serve the different requirements of drug discovery workflows.

AREAS COVERED

This paper introduced the key steps of the automatic data processing workflows for high-throughput MS technologies. Specific examples and requirements are detailed for different drug discovery applications.

EXPERT OPINION

The demand for automatic data processing in high-throughput mass spectrometry is driven by the need to keep pace with the accelerated speed of data acquisition. The seamless integration of processing capabilities with LIMS, efficient data review mechanisms, and the exploration of future features such as real-time feedback, automatic method optimization, and AI model training is crucial for advancing the drug discovery field. As technology continues to evolve, the synergy between high-throughput mass spectrometry and intelligent data processing will undoubtedly play a pivotal role in shaping the future of high-throughput drug discovery applications.

High-Throughput Compound Quality Assessment with High-Mass-Resolution Acoustic Ejection Mass Spectrometry: An Automatic Data Processing Toolkit

Pharmacological screening heavily relies on the reliability of compound libraries. To ensure the accuracy of screening results, fast and reliable quality control (QC) of these libraries is essential. While liquid chromatography (LC) with ultraviolet (UV) or mass spectrometry (MS) detection has been employed for molecule QC on small sample sets, the analytical throughput becomes a bottleneck when dealing with large libraries. Acoustic ejection mass spectrometry (AEMS) is a high-throughput analytical platform that covers a broad range of chemical structural space. In this study, we present the utilization of an AEMS system equipped with a high-resolution MS analyzer for high-throughput compound QC. To facilitate efficient data processing, which is a key challenge for such a high-throughput application, we introduce an automatic data processing toolkit that allows for the high-throughput assessment of the sample standards' quantitative and qualitative characteristics, including purity calculation with the background processing option. Moreover, the toolkit includes a module for quantitatively comparing spectral similarity with the reference library. Integrating the described high-resolution AEMS system with the data processing toolkit effectively eliminates the analytical bottleneck, enabling a rapid and reliable compound quality assessment of large-scale compound libraries.

Cell-free biosynthesis and engineering of ribosomally synthesized lanthipeptides

Ribosomally synthesized and post-translationally modified peptides (RiPPs) are a major class of natural products with diverse chemical structures and potent biological activities. A vast majority of RiPP gene clusters remain unexplored in microbial genomes, which is partially due to the lack of rapid and efficient heterologous expression systems for RiPP characterization and biosynthesis. Here, we report a unified biocatalysis (UniBioCat) system based on cell-free gene expression for rapid biosynthesis and engineering of RiPPs. We demonstrate UniBioCat by reconstituting a full biosynthetic pathway for de novo biosynthesis of salivaricin B, a lanthipeptide RiPP. Next, we delete several protease/peptidase genes from the source strain to enhance the performance of UniBioCat, which then can synthesize and screen salivaricin B variants with enhanced antimicrobial activity. Finally, we show that UniBioCat is generalizable by synthesizing and evaluating the bioactivity of ten uncharacterized lanthipeptides. We expect UniBioCat to accelerate the discovery, characterization, and synthesis of RiPPs.

Establishing a versatile toolkit of flux enhanced strains and cell extracts for pathway prototyping

Building and optimizing biosynthetic pathways in engineered cells holds promise to address societal needs in energy, materials, and medicine, but it is often time-consuming. Cell-free synthetic biology has emerged as a powerful tool to accelerate design-build-test-learn cycles for pathway engineering with increased tolerance to toxic compounds. However, most cell-free pathway prototyping to date has been performed in extracts from wildtype cells which often do not have sufficient flux towards the pathways of interest, which can be enhanced by engineering. Here, to address this gap, we create a set of engineered Escherichia coli and Saccharomyces cerevisiae strains rewired via CRISPR-dCas9 to achieve high-flux toward key metabolic precursors; namely, acetyl-CoA, shikimate, triose-phosphate, oxaloacetate, α-ketoglutarate, and glucose-6-phosphate. Cell-free extracts generated from these strains are used for targeted enzyme screening in vitro. As model systems, we assess in vivo and in vitro production of triacetic acid lactone from acetyl-CoA and muconic acid from the shikimate pathway. The need for these platforms is exemplified by the fact that muconic acid cannot be detected in wildtype extracts provided with the same biosynthetic enzymes. We also perform metabolomic comparison to understand biochemical differences between the cellular and cell-free muconic acid synthesis systems (E. coli and S. cerevisiae cells and cell extracts with and without metabolic rewiring). While any given pathway has different interfaces with metabolism, we anticipate that this set of pre-optimized, flux enhanced cell extracts will enable prototyping efforts for new biosynthetic pathways and the discovery of biochemical functions of enzymes.

Combining Cell-Free Expression and Multifactor Optimization for Enhanced Biosynthesis of Cinnamyl Alcohol

Cell-free expression systems have emerged as a potent and promising platform for the biosynthesis of chemicals by reconstituting in vitro expressed enzymes. Here, we report cell-free biosynthesis of cinnamyl alcohol (cinOH) with enhanced productivity by using the Plackett-Burman experimental design for multifactor optimization. Initially, four enzymes were individually expressed in vitro and directly mixed to reconstitute a biosynthetic route for the synthesis of cinOH. Then, the Plackett-Burman experimental design was used to screen multiple reaction factors and found three crucial parameters (i.e., reaction temperature, reaction volume, and carboxylic acid reductase) for the cinOH production. With the optimum reaction conditions, approximately 300 μM of cinOH was synthesized after 10 h of cell-free biosynthesis. Extending the production time to 24 h also increased the production to a maximum yield of 807 μM, which is nearly 10 times higher than the initial yield without optimization. This study demonstrates that cell-free biosynthesis can be combined with other powerful optimization methodologies such as the Plackett-Burman experimental design for enhanced production of valuable chemicals.

Rewiring cell-free metabolic flux in E. coli lysates using a block-push-pull approach

Cell-free systems can expedite the design and implementation of biomanufacturing processes by bypassing troublesome requirements associated with the use of live cells. In particular, the lack of survival objectives and the open nature of cell-free reactions afford engineering approaches that allow purposeful direction of metabolic flux. The use of lysate-based systems to produce desired small molecules can result in competitive titers and productivities when compared to their cell-based counterparts. However, pathway crosstalk within endogenous lysate metabolism can compromise conversion yields by diverting carbon flow away from desired products. Here, the 'block-push-pull' concept of conventional cell-based metabolic engineering was adapted to develop a cell-free approach that efficiently directs carbon flow in lysates from glucose and toward endogenous ethanol synthesis. The approach is readily adaptable, is relatively rapid and allows for the manipulation of central metabolism in cell extracts. In implementing this approach, a block strategy is first optimized, enabling selective enzyme removal from the lysate to the point of eliminating by-product-forming activity while channeling flux through the target pathway. This is complemented with cell-free metabolic engineering methods that manipulate the lysate proteome and reaction environment to push through bottlenecks and pull flux toward ethanol. The approach incorporating these block, push and pull strategies maximized the glucose-to-ethanol conversion in an Escherichia coli lysate that initially had low ethanologenic potential. A 10-fold improvement in the percent yield is demonstrated. To our knowledge, this is the first report of successfully rewiring lysate carbon flux without source strain optimization and completely transforming the consumed input substrate to a desired output product in a lysate-based, cell-free system.

Biomacromolecule-Assisted Screening for Reaction Discovery and Catalyst Optimization

Reaction discovery and catalyst screening lie at the heart of synthetic organic chemistry. While there are efforts at de novo catalyst design using computation/artificial intelligence, at its core, synthetic chemistry is an experimental science. This review overviews biomacromolecule-assisted screening methods and the follow-on elaboration of chemistry so discovered. All three types of biomacromolecules discussed─enzymes, antibodies, and nucleic acids─have been used as "sensors" to provide a readout on product chirality exploiting their native chirality. Enzymatic sensing methods yield both UV-spectrophotometric and visible, colorimetric readouts. Antibody sensors provide direct fluorescent readout upon analyte binding in some cases or provide for cat-ELISA (Enzyme-Linked ImmunoSorbent Assay)-type readouts. DNA biomacromolecule-assisted screening allows for templation to facilitate reaction discovery, driving bimolecular reactions into a pseudo-unimolecular format. In addition, the ability to use DNA-encoded libraries permits the barcoding of reactants. All three types of biomacromolecule-based screens afford high sensitivity and selectivity. Among the chemical transformations discovered by enzymatic screening methods are the first Ni(0)-mediated asymmetric allylic amination and a new thiocyanopalladation/carbocyclization transformation in which both C-SCN and C-C bonds are fashioned sequentially. Cat-ELISA screening has identified new classes of sydnone-alkyne cycloadditions, and DNA-encoded screening has been exploited to uncover interesting oxidative Pd-mediated amido-alkyne/alkene coupling reactions.

Cell-free prototyping enables implementation of optimized reverse β-oxidation pathways in heterotrophic and autotrophic bacteria

Carbon-negative synthesis of biochemical products has the potential to mitigate global CO₂ emissions. An attractive route to do this is the reverse β-oxidation (r-BOX) pathway coupled to the Wood-Ljungdahl pathway. Here, we optimize and implement r-BOX for the synthesis of C4-C6 acids and alcohols. With a high-throughput in vitro prototyping workflow, we screen 762 unique pathway combinations using cell-free extracts tailored for r-BOX to identify enzyme sets for enhanced product selectivity. Implementation of these pathways into Escherichia coli generates designer strains for the selective production of butanoic acid (4.9 ± 0.1 gL⁻¹), as well as hexanoic acid (3.06 ± 0.03 gL⁻¹) and 1-hexanol (1.0 ± 0.1 gL⁻¹) at the best performance reported to date in this bacterium. We also generate Clostridium autoethanogenum strains able to produce 1-hexanol from syngas, achieving a titer of 0.26 gL⁻¹ in a 1.5 L continuous fermentation. Our strategy enables optimization of r-BOX derived products for biomanufacturing and industrial biotechnology.

An attractive route for carbon-negative synthesis of biochemical products is the reverse β-oxidation pathway coupled to the Wood-Ljungdahl pathway. Here the authors use a high-throughput in vitro prototyping workflow to screen 762 unique pathway combinations using cell-free extracts tailored for r-BOX to identify enzyme sets for enhanced product selectivity.

Cell-Free Protein Synthesis for High-Throughput Biosynthetic Pathway Prototyping

Biological systems provide a sustainable and complimentary approach to synthesizing useful chemical products. Metabolic engineers seeking to establish economically viable biosynthesis platforms strive to increase product titers, rates, and yields. Despite continued advances in genetic tools and metabolic engineering techniques, cellular workflows remain limited in throughput. It may take months to test dozens of unique pathway designs even in a robust model organism, such as Escherichia coli. In contrast, cell-free protein synthesis enables the rapid generation of enzyme libraries that can be combined to reconstitute metabolic pathways in vitro for biochemical synthesis in days rather than weeks. Cell-free reactions thereby enable comparison of hundreds to thousands of unique combinations of enzyme homologs and concentrations, which can quickly identify the most productive pathway variants to test in vivo or further characterize in vitro. This cell-free pathway prototyping strategy provides a complementary approach to accelerate cellular metabolic engineering efforts toward highly productive strains for metabolite production.

Using measures of metabolic flux to align screening and clinical development: Avoiding pitfalls to enable translational studies

Screening campaigns, especially those aimed at modulating enzyme activity, often rely on measuring substrate→product conversions. Unfortunately, the presence of endogenous substrates and/or products can limit one's ability to measure conversions. As well, coupled detection systems, often used to facilitate optical readouts, are subject to interference. Stable isotope labeled substrates can overcome background contamination and yield a direct readout of enzyme activity. Not only can isotope kinetic assays enable early screening, but they can also be used to follow hit progression in translational (pre)clinical studies. Herein, we consider a case study surrounding lipid biology to exemplify how metabolic flux analyses can connect stages of drug development, caveats are highlighted to ensure reliable data interpretations. For example, when measuring enzyme activity in early biochemical screening it may be enough to quantify the formation of a labeled product. In contrast, cell-based and in vivo studies must account for variable exposure to a labeled substrate (or precursor) which occurs via tracer dilution and/or isotopic exchange. Strategies are discussed to correct for these complications. We believe that measures of metabolic flux can help connect structure-activity relationships with pharmacodynamic mechanisms of action and determine whether mechanistically differentiated biophysical interactions lead to physiologically relevant outcomes. Adoption of this logic may allow research programs to (i) build a critical bridge between primary screening and (pre)clinical development, (ii) elucidate biology in parallel with screening and (iii) suggest a strategy aimed at in vivo biomarker development.

A roadmap for metagenomic enzyme discovery

Covering: up to 2021Metagenomics has yielded massive amounts of sequencing data offering a glimpse into the biosynthetic potential of the uncultivated microbial majority. While genome-resolved information about microbial communities from nearly every environment on earth is now available, the ability to accurately predict biocatalytic functions directly from sequencing data remains challenging. Compared to primary metabolic pathways, enzymes involved in secondary metabolism often catalyze specialized reactions with diverse substrates, making these pathways rich resources for the discovery of new enzymology. To date, functional insights gained from studies on environmental DNA (eDNA) have largely relied on PCR- or activity-based screening of eDNA fragments cloned in fosmid or cosmid libraries. As an alternative, shotgun metagenomics holds underexplored potential for the discovery of new enzymes directly from eDNA by avoiding common biases introduced through PCR- or activity-guided functional metagenomics workflows. However, inferring new enzyme functions directly from eDNA is similar to searching for a 'needle in a haystack' without direct links between genotype and phenotype. The goal of this review is to provide a roadmap to navigate shotgun metagenomic sequencing data and identify new candidate biosynthetic enzymes. We cover both computational and experimental strategies to mine metagenomes and explore protein sequence space with a spotlight on natural product biosynthesis. Specifically, we compare in silico methods for enzyme discovery including phylogenetics, sequence similarity networks, genomic context, 3D structure-based approaches, and machine learning techniques. We also discuss various experimental strategies to test computational predictions including heterologous expression and screening. Finally, we provide an outlook for future directions in the field with an emphasis on meta-omics, single-cell genomics, cell-free expression systems, and sequence-independent methods.

Mass Spectrometric Biosensing: A Powerful Approach for Multiplexed Analysis of Clinical Biomolecules

Rapid and sensitive detection of clinical biomolecules in a multiplexed fashion is of great importance for accurate diagnosis of diseases. Mass spectrometric (MS) approaches are exceptionally suitable for clinical analysis due to its high throughput, high sensitivity, and reliable qualitative and quantitative capabilities. To break through the bottleneck of MS technique for detecting high-molecular-weight substances with low ionization efficiency, the concept of mass spectrometric biosensing has been put forward by adopting mass spectrometric chips to recognize the targets and mass spectrometry to detect the signals switched by the recognition. In this review, the principle of mass spectrometric sensing, the construction of different mass tags used for biosensing, and the typical combination mode of mass spectrometric imaging (MSI) technique are summarized. Future perspectives including the design of portable matching platforms, exploitation of novel mass tags, development of effective signal amplification strategies, and standardization of MSI methodologies are proposed to promote the advancements and practical applications of mass spectrometric biosensing.

Probing N-Heterocyclic Carbene Surfaces with Laser Desorption Ionization Mass Spectrometry

The proliferation of N-heterocyclic carbene (NHC) self-assembled monolayers (SAMs) on gold surfaces stems from their exceptional stability compared to conventional thiol-SAMs. The prospect of biological applications for NHC-SAMs on gold shows the need for biocompatible techniques (e.g., large biomolecule detection and high throughput) that assesses SAM molecular composition. Herein, we demonstrate that laser desorption ionization mass spectrometry (LDI-MS) is a powerful and facile probe of NHC surface chemistry. LDI-MS of prototypical imidazole-NHC- and benzimidazole-NHC-functionalized AuNPs yields exclusively [NHC₂Au]⁺ ions and not larger gold clusters. Employing benzimidazole-NHC isotopologues, we explore how monolayers pack on a single AuNP and the lability of the NHCs once ligated. Quantitative analysis of the homoleptic and heteroleptic [NHC₂Au]⁺ ions is performed by comparing to a binomial model representative of a randomized monolayer. Lastly, the reduction of nitro-NHC-AuNPs to amine-NHC-AuNPs is tracked via LDI-MS signals, illustrating the ability of LDI-MS to probe postsynthetic modifications of the anchored NHCs, which is critical for current and future applications of NHC surfaces.

High-Throughput Affinity Selection Mass Spectrometry Using SAMDI-MS to Identify Small-Molecule Binders of the Human Rhinovirus 3C Protease

Affinity selection mass spectrometry (ASMS) has emerged as a powerful high-throughput screening tool used in drug discovery to identify novel ligands against therapeutic targets. This report describes the first high-throughput screen using a novel self-assembled monolayer desorption ionization (SAMDI)-ASMS methodology to reveal ligands for the human rhinovirus 3C (HRV3C) protease. The approach combines self-assembled monolayers of alkanethiolates on gold with matrix-assisted laser desorption ionization time-of-flight (MALDI TOF) mass spectrometry (MS), a technique termed SAMDI-ASMS. The primary screen of more than 100,000 compounds in pools of 8 compounds per well was completed in less than 8 h, and informs on the binding potential and selectivity of each compound. Initial hits were confirmed in follow-up SAMDI-ASMS experiments in single-concentration and dose-response curves. The ligands identified by SAMDI-ASMS were further validated using differential scanning fluorimetry (DSF) and in functional protease assays against HRV3C and the related SARS-CoV-2 3CLpro enzyme. SAMDI-ASMS offers key benefits for drug discovery over traditional ASMS approaches, including the high-throughput workflow and readout, minimizing compound misbehavior by using smaller compound pools, and up to a 50-fold reduction in reagent consumption. The flexibility of this novel technology opens avenues for high-throughput ASMS assays of any target, thereby accelerating drug discovery for diverse diseases.

Acoustic Ejection Mass Spectrometry for High-Throughput Analysis

We describe a mass spectrometry (MS) analytical platform resulting from the novel integration of acoustic droplet ejection (ADE) technology, an open-port interface (OPI), and electrospray ionization (ESI)-MS that creates a transformative system enabling high-speed sampling and label-free analysis. The ADE technology delivers nanoliter droplets in a touchless manner with high speed, precision, and accuracy. Subsequent sample dilution within the OPI, in concert with the capabilities of modern ESI-MS, eliminates the laborious sample preparation and method development required in current approaches. This platform is applied to a variety of experiments, including high-throughput (HT) pharmacology screening, label-free in situ enzyme kinetics, in vitro absorption, distribution, metabolism, elimination, pharmacokinetic and biomarker analysis, and HT parallel medicinal chemistry.

Rapid in vitro prototyping of O-methyltransferases for pathway applications in Escherichia coli

O-Methyltransferases are ubiquitous enzymes involved in biosynthetic pathways for secondary metabolites such as bacterial antibiotics, human catecholamine neurotransmitters, and plant phenylpropanoids. While thousands of putative O-methyltransferases are found in sequence databases, few examples are functionally characterized. From a pathway engineering perspective, however, it is crucial to know the substrate and product ranges of the respective enzymes to fully exploit their catalytic power. In this study, we developed an in vitro prototyping workflow that allowed us to screen ∼30 enzymes against five substrates in 3 days with high reproducibility. We combined in vitro transcription/translation of the genes of interest with a microliter-scale enzymatic assay in 96-well plates. The substrate conversion was indirectly measured by quantifying the consumption of the S-adenosyl-L-methionine co-factor by time-resolved fluorescence resonance energy transfer rather than time-consuming product analysis by chromatography. This workflow allowed us to rapidly prototype thus far uncharacterized O-methyltransferases for future use as biocatalysts.

Label-Free Screening of SARS-CoV-2 NSP14 Exonuclease Activity Using SAMDI Mass Spectrometry

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the virus responsible for the global COVID-19 pandemic. Nonstructural protein 14 (NSP14), which features exonuclease (ExoN) and guanine N7 methyltransferase activity, is a critical player in SARS-CoV-2 replication and fidelity and represents an attractive antiviral target. Initiating drug discovery efforts for nucleases such as NSP14 remains a challenge due to a lack of suitable high-throughput assay methodologies. This report describes the combination of self-assembled monolayers and matrix-assisted laser desorption ionization mass spectrometry to enable the first label-free and high-throughput assay for NSP14 ExoN activity. The assay was used to measure NSP14 activity and gain insight into substrate specificity and the reaction mechanism. Next, the assay was optimized for kinetically balanced conditions and miniaturized, while achieving a robust assay (Z factor > 0.8) and a significant assay window (signal-to-background ratio > 200). Screening 10,240 small molecules from a diverse library revealed candidate inhibitors, which were counterscreened for NSP14 selectivity and RNA intercalation. The assay methodology described here will enable, for the first time, a label-free and high-throughput assay for NSP14 ExoN activity to accelerate drug discovery efforts and, due to the assay flexibility, can be more broadly applicable for measuring other enzyme activities from other viruses or implicated in various pathologies.

Development of a Novel Label-Free and High-Throughput Arginase-1 Assay Using Self-Assembled Monolayer Desorption Ionization Mass Spectrometry

Arginase-1, an enzyme that catalyzes the reaction of L-arginine to L-ornithine, is implicated in the tumor immune response and represents an interesting therapeutic target in immuno-oncology. Initiating arginase drug discovery efforts remains a challenge due to a lack of suitable high-throughput assay methodologies. This report describes the combination of self-assembled monolayers and matrix-assisted laser desorption ionization mass spectrometry to enable the first label-free and high-throughput assay for arginase activity. The assay was optimized for kinetically balanced conditions and miniaturized, while achieving a robust assay (Z-factor > 0.8) and a significant assay window [signal-to-background ratio > 20] relative to fluorescent approaches. To validate the assay, the inhibition of the reference compound nor-NOHA (Nω-hydroxy-nor-L-arginine) was evaluated, and the IC₅₀ measured to be in line with reported results (IC₅₀ = 180 nM). The assay was then used to complete a screen of 175,000 compounds, demonstrating the high-throughput capacity of the approach. The label-free format also eliminates opportunities for false-positive results due to interference from library compounds and optical readouts. The assay methodology described here enables new opportunities for drug discovery for arginase and, due to the assay flexibility, can be more broadly applicable for measuring other amino acid-metabolizing enzymes.

Cell-Free Exploration of the Natural Product Chemical Space

Natural products and secondary metabolites comprise an indispensable resource from living organisms that have transformed areas of medicine, agriculture, and biotechnology. Recent advances in high-throughput DNA sequencing and computational analysis suggest that the vast majority of natural products remain undiscovered. To accelerate the natural product discovery pipeline, cell-free metabolic engineering approaches used to develop robust catalytic networks are being repurposed to access new chemical scaffolds, and new enzymes capable of performing diverse chemistries. Such enzymes could serve as flexible biocatalytic tools to further expand the unique chemical space of natural products and secondary metabolites, and provide a more sustainable route to manufacture these molecules. Herein, we highlight select examples of natural product biosynthesis using cell-free systems and propose how cell-free technologies could facilitate our ability to access and modify these structures to transform synthetic and chemical biology.

High Throughput Screening with SAMDI Mass Spectrometry for Directed Evolution

Advances in directed evolution have led to an exploration of new and important chemical transformations; however, many of these efforts still rely on the use of low-throughput chromatography-based screening methods. We present a high-throughput strategy for screening libraries of enzyme variants for improved activity. Unpurified reaction products are immobilized to a self-assembled monolayer and analyzed by mass spectrometry, allowing for direct evaluation of thousands of variants in under an hour. The method was demonstrated with libraries of randomly mutated cytochrome P411 variants to identify improved catalysts for C-H alkylation. The technique may be tailored to evolve enzymatic activity for a variety of transformations where higher throughput is needed.

Targeted Growth Medium Dropouts Promote Aromatic Compound Synthesis in Crude E. coli Cell-Free Systems

Progress in cell-free protein synthesis (CFPS) has spurred resurgent interest in engineering complex biological metabolism outside of the cell. Unlike purified enzyme systems, crude cell-free systems can be prepared for a fraction of the cost and contain endogenous cellular pathways that can be activated for biosynthesis. Endogenous activity performs essential functions in cell-free systems including substrate biosynthesis and energy regeneration; however, use of crude cell-free systems for bioproduction has been hampered by the under-described complexity of the metabolic networks inherent to a crude lysate. Physical and chemical cultivation parameters influence the endogenous activity of the resulting lysate, but targeted efforts to engineer this activity by manipulation of these nongenetic factors has been limited. Here growth medium composition was manipulated to improve the one-pot in vitro biosynthesis of phenol from glucose via the expression of Pasteurella multocida phenol-tyrosine lyase in crude E. coli lysates. Crude cell lysate metabolic activity was focused toward the limiting precursor tyrosine by targeted growth medium dropouts guided by proteomics. The result is the activation of a 25-step enzymatic reaction cascade involving at least three endogenous E. coli metabolic pathways. Additional modification of this system, through CFPS of feedback intolerant AroG improves yield. This effort demonstrates the ability to activate a long, complex pathway in vitro and provides a framework for harnessing the metabolic potential of diverse organisms for cell-free metabolic engineering. The more than 6-fold increase in phenol yield with limited genetic manipulation demonstrates the benefits of optimizing growth medium for crude cell-free extract production and illustrates the advantages of a systems approach to cell-free metabolic engineering.

Harnessing in vitro platforms for natural product research: in vitro driven rational engineering and mining (iDREAM)

Well-known issues amid in vivo research of natural product discovery and overproduction, such as unculturable or unmanipulable microorganisms, labor-intensive experimental cycles, and hidden rate-limiting steps, have hampered relevant investigations. To overcome these long-standing challenges, many researchers are turning toward in vitro platforms, which bypass the complicated cellular machinery and simplify the study of natural products. Here, we summarize the in vitro driven rational engineering and mining (iDREAM) strategy, which harnesses the flexibility and controllability of in vitro systems to rationally overproduce commodity chemicals and efficiently mine novel compounds. The iDREAM strategy promises to make further significant contributions toward both fundamental advances and industrial practices.

Evaluation of SARS-CoV-2 3C-like protease inhibitors using self-assembled monolayer desorption ionization mass spectrometry

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of the COVID-19 pandemic that began in 2019. The coronavirus 3-chymotrypsin-like cysteine protease (3CLpro) controls replication and is therefore considered a major target for antiviral discovery. This study describes the evaluation of SARS-CoV-2 3CLpro inhibitors in a novel self-assembled monolayer desorption ionization mass spectrometry (SAMDI-MS) enzymatic assay. Compared with a traditional FRET readout, the label-free SAMDI-MS assay offers greater sensitivity and eliminates false positive inhibition from compound interference with the optical signal. The SAMDI-MS assay was optimized and validated with known inhibitors of coronavirus 3CLpro such as GC376 (IC50 = 0.060 μM), calpain inhibitors II and XII (IC50 ~20-25 μM). The FDA-approved drugs shikonin, disulfiram, and ebselen did not inhibit SARS-CoV-2 3CLpro activity in the SAMDI-MS assay under physiologically relevant reducing conditions. The three drugs did not directly inhibit human β-coronavirus OC-43 or SARS-CoV-2 in vitro, but instead induced cell death. In conclusion, the SAMDI-MS 3CLpro assay, combined with antiviral and cytotoxic assessment, provides a robust platform to evaluate antiviral agents directed against SARS-CoV-2.

Biological Materials: The Next Frontier for Cell-Free Synthetic Biology

Advancements in cell-free synthetic biology are enabling innovations in sustainable biomanufacturing, that may ultimately shift the global manufacturing paradigm toward localized and ecologically harmonized production processes. Cell-free synthetic biology strategies have been developed for the bioproduction of fine chemicals, biofuels and biological materials. Cell-free workflows typically utilize combinations of purified enzymes, cell extracts for biotransformation or cell-free protein synthesis reactions, to assemble and characterize biosynthetic pathways. Importantly, cell-free reactions can combine the advantages of chemical engineering with metabolic engineering, through the direct addition of co-factors, substrates and chemicals -including those that are cytotoxic. Cell-free synthetic biology is also amenable to automatable design cycles through which an array of biological materials and their underpinning biosynthetic pathways can be tested and optimized in parallel. Whilst challenges still remain, recent convergences between the materials sciences and these advancements in cell-free synthetic biology enable new frontiers for materials research.

Total in vitro biosynthesis of the nonribosomal macrolactone peptide valinomycin

Natural products are important because of their significant pharmaceutical properties such as antiviral, antimicrobial, and anticancer activity. Recent breakthroughs in DNA sequencing reveal that a great number of cryptic natural product biosynthetic gene clusters are encoded in microbial genomes, for example, those of Streptomyces species. However, it is still challenging to access compounds from these clusters because many source organisms are uncultivable or the genes are silent during laboratory cultivation. To address this challenge, we develop an efficient cell-free platform for the rapid, in vitro total biosynthesis of the nonribosomal peptide valinomycin as a model. We achieve this goal in two ways. First, we used a cell-free protein synthesis (CFPS) system to express the entire valinomycin biosynthetic gene cluster (>19 kb) in a single-pot reaction, giving rise to approximately 37 μg/L of valinomycin after optimization. Second, we coupled CFPS with cell-free metabolic engineering system by mixing two enzyme-enriched cell lysates to perform a two-stage biosynthesis. This strategy improved valinomycin production ~5000-fold to nearly 30 mg/L. We expect that cell-free biosynthetic systems will provide a new avenue to express, discover, and characterize natural product gene clusters of interest in vitro.

High-Throughput Synthesis and Analysis of Intact Glycoproteins Using SAMDI-MS

High-throughput quantification of the post-translational modification of many individual protein samples is challenging with current label-based methods. This paper demonstrates an efficient method that addresses this gap by combining Escherichia coli-based cell-free protein synthesis (CFPS) and self-assembled monolayers for matrix-assisted laser desorption/ionization mass spectrometry (SAMDI-MS) to analyze intact proteins. This high-throughput approach begins with polyhistidine-tagged protein substrates expressed from linear DNA templates by CFPS. Here, we synthesized an 87-member library of the E. coli Immunity Protein 7 (Im7) containing an acceptor sequence optimized for glycosylation by the Actinobacillus pleuropneumoniae N-glycosyltransferase (NGT) at every possible position along the protein backbone. These protein substrates were individually treated with NGT and then selectively immobilized to self-assembled monolayers presenting nickel-nitrilotriacetic acid (Ni-NTA) complexes before final analysis by SAMDI-MS to quantify the conversion of substrate to glycoprotein. This method offers new opportunities for rapid synthesis and quantitative evaluation of intact glycoproteins.

Enhancing control of cell-free metabolism through pH modulation

Engineering metabolism for the synthesis of bio-based products in non-model organisms can be challenging. One specific challenge is that biosynthetic pathways are often built from enzyme candidates sourced from diverse organisms, which can prove difficult to implement in recombinant hosts due to differences in their cellular environments (e.g. pH, cofactor balance). To address this problem, we report a cell-free synthetic biology approach for understanding metabolism in a range of environmental conditions, specifically under varied pH. The key idea is to control the pH of Escherichia coli-based cell-free systems for assessing pathway performance using enzymes sourced from organisms other than E. coli. As a model, we apply this approach to study the impact of pH on the n-butanol biosynthesis pathway derived from clostridia in E. coli lysates. Specifically, we exploit the open, cell-free reaction environment to explore pH outside the habitable range of E. coli, revealing insights into how chemical context impacts the interaction between native metabolism and heterologous enzymes. We find that the pH optimum for butanol production from acetyl-CoA is substantially lower than the optimal pH of glycolysis in E. coli-based crude lysates. In addition, pH is an essential factor to consider when activating metabolic pathways in the cell-free environment due to its effect on reaction yield or enzyme activity, the latter of which is demonstrated in this work for alcohol dehydrogenases from a range of extremophiles. Ultimately, altering metabolism through pH control will allow cell-free systems to be used in studying the metabolic state of organisms and identify suitable enzymes for pathway engineering.