Name: liquid chromatography coupled to refractive index or mass spectrometric detection for metabolite profiling in lysate-based cell-free systems
Uploaded: 2021-09-23T14:45:00
Duration: 14 min 42 s
Description: Watch this Scientific Journal Video about Liquid Chromatography Coupled to Refractive Index or Mass Spectrometric Detection for Metabolite Profiling in Lysate-based Cell-free Systems at JoVE.com

This research was sponsored by the Genomic Science Program, U.S. Department of Energy, Office of Science, Biological and Environmental Research, as part of the Plant Microbe Interfaces Scientific Focus Area (http://pmi.ornl.gov). Oak Ridge National Laboratory is managed by UT-Battelle, LLC, for the U.S. Department of Energy under contract DE-AC05-00OR22725. This manuscript has been authored by UT-Battelle, LLC under Contract DE-AC05- 00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).

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The authors declare that they have no known competing financial interests or other conflicts of interest.

The outlined HPLC-RID approach can be used to successfully quantify sugar substrate consumption and subsequent conversions to major organic acid and alcohol products of lysate central metabolism over time. Furthermore, this protocol employs a simple isocratic method using a single mobile phase, requires minimal sample preparation, and allows a simple targeted downstream analysis. Analytes measured by the HPLC-RID method are distinguished solely by their retention times, and therefore their interactions with the selected column resin. The HPLC column utilized here was particularly designed to separate carbohydrates, organic acids, and alcohols by combining size-exclusion and ligand exchange (i.e., ion-moderated partition chromatography). The described method is, therefore, useful for more targeted analysis of carbohydrate substrates and select end-products of glucose fermentation pathways which are expected to primarily facilitate and energize lysate-based bio-transformations8,15,21. However, this protocol does not account for the activation of other metabolic pathways in cell extracts. Pipelines employing other chromatographic separation techniques (i.e., hydrophilic interaction chromatography), gradient elution methods, more complicated sample preparation (i.e., derivatization), and different optical detectors (e.g., ultraviolet light or evaporative light scattering detectors) could be used to detect other metabolites such as amino acids and sugar phosphates23,24. Alternatively, a global approach to studying lysate metabolism can be taken using LC-MS/MS.
The described LC-MS/MS method is a single workflow for measuring and identifying a broader range of metabolites. LC-MS/MS is a state-of-the-art analytical tool for metabolome profiling because of its sensitivity and ability to distinguish metabolites by retention time and m/z ratios with high resolution16. With a focus on central carbon metabolic pathways and amino acid anabolism, negative mode MS/MS was implemented to specifically detect polar organic acids, sugar phosphates, and amino acids. Coupled with a nano-liquid chromatography technique, the method provides high sensitivity for detecting small molecules in the complex lysate background17. In terms of profiling lysate-based CFME metabolism, however, a limitation of the described LC-MS/MS protocol is its lower detection limit of 50 m/z, which precludes the measurement of ethanol, a major product in lysate glucose metabolism, as well as formate, which are both otherwise easily quantified by the detailed HPLC-RID method. Compared to LC-MS/MS, HPLC-RID has the additional advantage of relative accessibility in terms of cost and difficulty. To the latter point, troubleshooting the LC-MS/MS method described here may require some degree of expertise in mass spectrometry. Nonetheless, MS detection has uniquely appealing applications over RID as it can additionally distinguish labeled isotopes in metabolomes, an excellent technique for understanding carbon movement from supplemented substrates through the complex lysate metabolic network18. Such an approach was applied here by supplementing reactions with 13C6-glucose and analyzing the relative abundance values of downstream 13C-incorporating metabolites. The analysis allowed the definition of active and inactive pathways, supporting previously reported assumptions and providing new insights about metabolic flux in lysates. Modifications can also be made within the method for specific analyses. For example, standard solutions of 13C-labeled target compounds can be analyzed along with samples to achieve absolute quantitative measurements of glucose-derived molecules over time and make conclusions about flux distributions. Better detection of positively charged compounds can also be enabled within the current workflow by running sequences with .meth files adjusted for positive mode detection.
Analytical sampling in both described methods is conveniently automated, ensuring high reproducibility. Moreover, smooth analytical runs can be expected as long as proper instrument handling practices and maintenance are observed. When using these tools to analyze CFME reactions, more critical considerations&#160;should be made upstream and downstream of sampling. During sample preparation, it is important that time-course controls are representative of time-zero. Here, proteins were precipitated in lysates by acidification to stop metabolic reactions. For time-zero samples, the acid solvent was combined with lysate prior to adding the reaction mix containing glucose. Acidification with trichloroacetic acid effectively ensured that glucose is not metabolized at time-zero, as shown in the HPLC-RID data (Figure 2). While a similar procedure to quench glucose metabolism was performed in the reported LC-MS/MS analysis, 13C-labeled metabolites were detected in time-zero samples, albeit at significantly low abundance values relative to samples extracted at later timepoints. Moreover, these observations were limited to intermediates of glycolysis. The data suggest that the reactions retain some degree of glycolytic activity after acidification with the extraction solvent that is detected by this highly sensitive method. The extent of this activity, however, should be quantified. A previous study reported that acidic extraction solvents may not sufficiently quench intermediate glycolytic reactions but can stop significant glucose consumption10. While this remains to be further investigated in the system used here, drastic changes in relative abundance values between time-zero and later timepoint samples can be interpreted as trends in glucose metabolism. Exploring alternative quenching methods, however, is recommended in similar applications, specifically for obtaining absolute quantities of metabolic intermediates10. Furthermore, good practices during downstream software analyses should also be observed. Consistency is imperative when manually integrating peak areas from RID signals to reduce human error. Manual integration should also be applied to peak areas of standards whenever manually integrated peak areas are being used to quantify metabolite concentrations in samples. Throughout the targeted LC-MS/MS analysis, tentative annotations from MZmine analysis should be validated by manual peak checking using an MS quality browser, and m/z features should only be annotated when calculated mass errors are acceptable. Here, these analyses were performed manually for a limited set of targets since comprehensive and robust software for isotope searching is not yet established. However, such automated methods for searching 13C labeled metabolites are currently emerging and would streamline more complicated analyses as well, like profiling lysates beyond central carbon metabolism25.
Advanced liquid chromatography is a robust and widely applied method for separating small molecules in complex metabolic mixtures11. The described methods couple this separation technique with the refractive index or mass spectrometric detection to successfully analyze metabolite conversions in lysate-based CFME reactions. HPLC-RID and LC-MS/MS are individually powerful tools for profiling active lysate metabolism, and their complementarity can further be leveraged to address each technique&#39;s inherent limitations. The reported methods enable the application and development of CFME as they can be utilized to understand lysate metabolism, monitor improvements in targeted metabolite conversions, and elucidate alterations to metabolite flux when manipulating lysate metabolism.

Limitations in engineering microbes for chemical production can be addressed by recapitulating biochemical reactions in vitro where competing cellular survival functions are absent1. Moreover, the open reaction environment (i.e., absence of a cell membrane) is more amenable to manipulation and is easier to monitor compared to live cells. This foundational concept of cell-free metabolic engineering (CFME) has been elegantly demonstrated by the reconstitution of metabolic pathways to synthesize valuable chemicals like hydrogen and monoterpenes with production metrics that are orders of magnitude higher than presented in microbial cell factories thus far1,2,3. Methods for purifying whole pathways, however, are currently constrained by time and cost. Alternatively, cell-free metabolic systems can be derived from crude cell extracts through rapid and inexpensive methods relative to whole pathway reconstitution4. The central metabolism that is retained in cell extracts can be supplemented with energy substrates (e.g., glucose and enzymatic cofactors) and salts in buffered solutions to generate central metabolic precursors for over 24 h5,6. Adding exogenous enzymes to the lysate-based CFME reaction allows more complex bio-transformations of glucose into more valuable chemicals at high titers4,6,7. Although yield tends to be compromised in these systems due to their cell-like metabolic complexity, unique methods to curate lysate proteomes for higher yield conversion have been and are being developed7,8.
The ease of carrying out metabolic transformations in lysate-based cell-free systems makes these excellent platforms for either moving chemical manufacturing outside of the cell altogether or for prototyping new pathways with high throughput before building and testing these designs in vivo2,9. For either application, tools for monitoring metabolic conversions or observing overall alterations to metabolic flux in lysates are integral to the advancement of CFME. High-performance liquid chromatography (HPLC) can be used to separate the chemical constituents of CFME reactions with high-resolution and can be coupled to optical or mass-spectrometric detectors for metabolite quantification5,10. The underlying principle of HPLC is that analytes dissolved in a solvent (i.e., mobile phase) and pumped through a column will interact with the specific column packing material (i.e., stationary phase)11. Depending on their chemical properties, these analytes exhibit varying retention times before they are eventually eluted from the stationary phase and carried by the mobile phase to a detector. This report details the preparation and analysis of E. coli lysate-based CFME reactions through HPLC-based methods leveraging RID and MS/MS detection.
HPLC coupled to refractive index detection (HPLC-RID) is a generally accessible method for quickly identifying central metabolic precursors and end-products. Briefly, RID measures how analytes change the deflection of light by the mobile phase12. RID signals corresponding to target analytes in samples can then be quantified by comparisons with RID signals of standard solutions. In CFME applications, this mode of detection has been most commonly used with HPLC columns that separate compounds based on a combination of size exclusion and ligand exchange mechanisms, or ion-moderated partition chromatography5,6,8,13. This particular technique is used to quickly quantify the consumption of sugar substrates like glucose as well as the formation of fermentation products like succinate, lactate, formate, acetate, and ethanol in lysate-based CFME reactions8. Recording the concentration changes of these compounds via HPLC has been useful for both elucidating the potential of crude cell extracts to pool central metabolic precursors and understanding how pathway flux is redirected through fermentative pathways during complex metabolic conversions from glucose in lysates6,8,14. Seminal CFME studies in E. coli cell extracts confirm that fermentation compounds accumulate as end-products of glucose catabolism and also occur as unwanted by-products in lysates that overexpress exogenous enzymes6,15. It is suggested that fermentative metabolism plays a necessary role in regenerating redox equivalents of cofactors (i.e., NAD(P)H and ATP) to sustain glycolytic reactions8. Hence, an HPLC-based optical detection method designed to separate fermentation products is a useful and commonly applied tool when executing various lysate-based CFME tasks.
CFME can be implemented to accumulate metabolic end-products that are not carbohydrates, organic acids, or alcohols4. The measurement of intermediates that are consumed as quickly as they are synthesized may also be desirable10. While HPLC-RID is accessible in terms of cost and difficulty, this method is constrained by its ability to only distinguish metabolites based on retention time. A broader range of metabolites can be analyzed when liquid chromatography is coupled to MS/MS detection (LC-MS/MS)16. By this method, analytes in the mobile phase are ionized and differentially detected based on each molecule&#39;s mass and charge properties. Knowledge of both the metabolite&#39;s mass-to-charge (m/z) ratio and retention time on the column thus facilitates the separation of most metabolic intermediates and end-products with high resolution16. This detection technique can also be coupled to nano-liquid chromatography, which affords much lower flow rates and sample injection volumes, allowing more sensitive detection of small molecules in the complex lysate background17. LC-MS/MS can additionally be applied with isotope labeling since incorporated labels impart changes in analytes&#39; m/z values18. Timepoint measurements extracted from a CFME reaction supplemented with a 13C6-glucose substrate can thus determine the end- or by-products derived specifically from supplemented glucose. Although this isotope tracing method is not yet commonly applied in CFME studies, it is a powerful tool for understanding metabolic conversions in lysate-based CFME systems, specifically since salt counterions (i.e., acetate and glutamate) in these reactions are also catabolized as secondary substrates19. Leveraging this technique can thus draw a comprehensive picture of glucose metabolism in lysates, which to this day is not completely understood. Here, the protocol details a method for nano-liquid chromatography coupled to nanoelectrospray ionization (nano ESI) MS/MS that can be used to interrogate a possible model of glucose metabolism, specifically in E. coli lysates (Figure 1). The model is based on reports of fermentative pathways and the pentose phosphate pathway being active in E. coli lysates derived from strains grown in rich media5,6,8,14. The technique is additionally used to investigate amino acid production since current knowledge on amino acid anabolism from glucose in lysates is limited to a few examples such as the synthesis of aromatic amino acids7. Given the mostly polar nature of end-products and intermediates in these pathways (i.e., organic acids, sugar phosphates, and amino acids), reverse-phased liquid chromatography was utilized here. This technique separates polar compounds by elution from a nonpolar stationary phase. These compounds were then ionized by nano ESI in negative ion mode which permits the detection of analytes with at least one negative elementary charge and is thus useful for detecting acidic compounds. This technique is employed here to analyze glucose-derived 13C-incorporating metabolites and demonstrates the utility of LC-MS/MS for understanding glucose metabolism in lysates.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>0.22 &#956;m centrifuge tube filters (spin columns)</td>
			<td>Corning Costar</td>
			<td>8160</td>
			<td></td>
		</tr>
		<tr>
			<td>1.5 mL microcentrifuge tubes</td>
			<td>VWR</td>
			<td>87003-294</td>
			<td></td>
		</tr>
		<tr>
			<td>1260 Infinity Binary LC Pump</td>
			<td>Agilent</td>
			<td>G1312B</td>
			<td>HPLC-RID system</td>
		</tr>
		<tr>
			<td>1260 Infinity High Performance Degasser</td>
			<td>Agilent</td>
			<td>G4225A</td>
			<td>HPLC-RID system</td>
		</tr>
		<tr>
			<td>1260 Infinity Refractive Index Detector</td>
			<td>Agilent</td>
			<td>G7162A</td>
			<td>HPLC-RID system</td>
		</tr>
		<tr>
			<td>1260 Infinity Standard Autosampler</td>
			<td>Agilent</td>
			<td>G1329B</td>
			<td>HPLC-RID system</td>
		</tr>
		<tr>
			<td>13C6-glucose</td>
			<td>Sigma-Aldrich</td>
			<td>389374</td>
			<td>CFME reaction mix component (LC-MS/MS)</td>
		</tr>
		<tr>
			<td>500 mL 0.20 &#956;m pore (PES membrane) filter</td>
			<td>VWR</td>
			<td>10040-436</td>
			<td></td>
		</tr>
		<tr>
			<td>Acetonitrile (LC/MS grade)</td>
			<td>Fisher Scientific</td>
			<td>A955</td>
			<td>Solvent preparation for LC-MS/MS</td>
		</tr>
		<tr>
			<td>Adenosine triphosphate</td>
			<td>Sigma-Aldrich</td>
			<td>A7699</td>
			<td>CFME reaction mix component</td>
		</tr>
		<tr>
			<td>Aminex HPX 87-H column</td>
			<td>Bio-rad</td>
			<td>1250140</td>
			<td>Chromatography column for HPLC-RID</td>
		</tr>
		<tr>
			<td>Ammonium acetate (LC/MS grade)</td>
			<td>Fisher Scientific</td>
			<td>A11450</td>
			<td>Solvent preparation for LC-MS/MS</td>
		</tr>
		<tr>
			<td>Ammonium glutamate</td>
			<td>Sigma-Aldrich</td>
			<td>G1376</td>
			<td>CFME reaction mix component</td>
		</tr>
		<tr>
			<td>Autosampler vial caps (yellow, snap)</td>
			<td>Thermo Scientific</td>
			<td>C4011-50Y</td>
			<td>Sample storage/delivery for LC-MS/MS</td>
		</tr>
		<tr>
			<td>Autosampler vials (0.30 mL, polypropylene)</td>
			<td>Wheaton</td>
			<td>W225181</td>
			<td>Sample storage/delivery for LC-MS/MS</td>
		</tr>
		<tr>
			<td>Benchtop microcentrifuge</td>
			<td>Fisher Scientific</td>
			<td>13-100-675</td>
			<td></td>
		</tr>
		<tr>
			<td>Bis-Tris</td>
			<td>Sigma-Aldrich</td>
			<td>B9754</td>
			<td>CFME reaction mix component</td>
		</tr>
		<tr>
			<td>Coenzyme A (CoA)</td>
			<td>Sigma-Aldrich</td>
			<td>C4282</td>
			<td>CFME reaction mix component</td>
		</tr>
		<tr>
			<td>D-dextrose (Glucose)</td>
			<td>VWR</td>
			<td>BDH9230</td>
			<td>CFME reaction mix component</td>
		</tr>
		<tr>
			<td>Dipotassium phosphate</td>
			<td>Sigma-Aldrich</td>
			<td>P8281</td>
			<td>CFME reaction mix component</td>
		</tr>
		<tr>
			<td>Ethanol</td>
			<td>Fisher Scientific</td>
			<td>BP2818100</td>
			<td>Dissolved in S30 buffer for standard curve solution preparation (HPLC-RID)</td>
		</tr>
		<tr>
			<td>Formic acid (LC/MS grade)</td>
			<td>Thermo Scientific</td>
			<td>85178</td>
			<td>Solvent preparation for LC-MS/MS</td>
		</tr>
		<tr>
			<td>Fused silica (internal diameter of 100 &#956;m, external diameter of 375 &#956;m)</td>
			<td>Polymicro Technologies</td>
			<td>WM22005-ND</td>
			<td>Chromatography column for LC-MS/MS</td>
		</tr>
		<tr>
			<td>Glacial acetic acid</td>
			<td>Sigma-Aldrich</td>
			<td>A6283</td>
			<td>S30 buffer ingredient</td>
		</tr>
		<tr>
			<td>Isopropanol (LC/MS grade)</td>
			<td>Fisher Scientific</td>
			<td>A461</td>
			<td>Solvent preparation for LC-MS/MS</td>
		</tr>
		<tr>
			<td>Kinetex 5 &#956;m C18 stationary phase (100 &#197;)</td>
			<td>Phenomenex</td>
			<td>N/A; special order</td>
			<td>Chromatography column for LC-MS/MS</td>
		</tr>
		<tr>
			<td>LTQ Orbitrap Velos Pro Mass Spectrometer</td>
			<td>ThermoFisher Scientific</td>
			<td>N/A; special order</td>
			<td>Mass spectrometer for LC-MS/MS</td>
		</tr>
		<tr>
			<td>Magnesium acetate</td>
			<td>Sigma-Aldrich</td>
			<td>M5661</td>
			<td>S30 buffer ingredient</td>
		</tr>
		<tr>
			<td>Magnesium glutamate</td>
			<td>Sigma-Aldrich</td>
			<td>49605</td>
			<td>CFME reaction mix component</td>
		</tr>
		<tr>
			<td>Methanol (LC/MS grade)</td>
			<td>Fisher Scientific</td>
			<td>A456</td>
			<td>Solvent preparation for LC-MS/MS</td>
		</tr>
		<tr>
			<td>NAD+</td>
			<td>Sigma-Aldrich</td>
			<td>N0632</td>
			<td>CFME reaction mix component</td>
		</tr>
		<tr>
			<td>Nanospray Ionization Source</td>
			<td>ThermoFisher Scientific/Proxeon</td>
			<td>ES071 (newest model)</td>
			<td>Mass spectrometer for LC-MS/MS</td>
		</tr>
		<tr>
			<td>OpenLab CDS (Online) Software</td>
			<td>Agilent</td>
			<td>Version 2.15.26</td>
			<td>Chromatography Data System for acquiring and analyzing HPLC data</td>
		</tr>
		<tr>
			<td>Orbitrap Velos Pro LTQ Tune Plus Software</td>
			<td>Thermo</td>
			<td>Version 2.7</td>
			<td>Software for tuning the LC-MS/MS system</td>
		</tr>
		<tr>
			<td>Potassium acetate</td>
			<td>Sigma-Aldrich</td>
			<td>P1190</td>
			<td>S30 buffer ingredient</td>
		</tr>
		<tr>
			<td>Potassium glutamate</td>
			<td>Sigma-Aldrich</td>
			<td>G1501</td>
			<td>CFME reaction mix component</td>
		</tr>
		<tr>
			<td>Refrigerated centrifuge</td>
			<td>Eppendorf</td>
			<td>5415 C</td>
			<td></td>
		</tr>
		<tr>
			<td>Screw caps (with septa, 9 mm)</td>
			<td>Supelco</td>
			<td>29315-U</td>
			<td>Sample storage/delivery for HPLC-RID</td>
		</tr>
		<tr>
			<td>Screwthread glass vials (2 mL)</td>
			<td>Supelco</td>
			<td>29376-U</td>
			<td>Sample storage/delivery for HPLC-RID</td>
		</tr>
		<tr>
			<td>Sodium acetate</td>
			<td>Sigma-Aldrich</td>
			<td>241245</td>
			<td>Dissolved in S30 buffer for standard curve solution preparation (HPLC-RID)</td>
		</tr>
		<tr>
			<td>Sodium formate</td>
			<td>Sigma-Aldrich</td>
			<td>247596</td>
			<td>Dissolved in S30 buffer for standard curve solution preparation (HPLC-RID)</td>
		</tr>
		<tr>
			<td>Sodium lactate</td>
			<td>Sigma-Aldrich</td>
			<td>71716</td>
			<td>Dissolved in S30 buffer for standard curve solution preparation (HPLC-RID)</td>
		</tr>
		<tr>
			<td>Succinic acid</td>
			<td>Sigma-Aldrich</td>
			<td>398055</td>
			<td>Dissolved in S30 buffer for standard curve solution preparation (HPLC-RID)</td>
		</tr>
		<tr>
			<td>Sulfuric acid</td>
			<td>Sigma-Aldrich</td>
			<td>258105</td>
			<td>Solvent preparation for HPLC-RID</td>
		</tr>
		<tr>
			<td>Trichloroacetic acid</td>
			<td>Sigma-Aldrich</td>
			<td>T6399</td>
			<td></td>
		</tr>
		<tr>
			<td>Tris-acetate</td>
			<td>GoldBio</td>
			<td>T-090-100</td>
			<td>S30 buffer ingredient</td>
		</tr>
		<tr>
			<td>Ultimate 3000 LC with autosampler</td>
			<td>Dionex</td>
			<td>Solvent Rack: SRD-3600</td>
			<td>Liquid chromatography system for LC-MS/MS analysis</td>
		</tr>
		<tr>
			<td>Ultimate 3000 LC with autosampler</td>
			<td>Dionex</td>
			<td>Rapid Separation Binary Pump: HPG-3400RS</td>
			<td>Liquid chromatography system for LC-MS/MS analysis</td>
		</tr>
		<tr>
			<td>Ultimate 3000 LC with autosampler</td>
			<td>Dionex</td>
			<td>Rapid Separation Well Plate Autosampler: WPS-3000TRS</td>
			<td>Liquid chromatography system for LC-MS/MS analysis</td>
		</tr>
		<tr>
			<td>Water (LC/MS grade)</td>
			<td>Fisher Scientific</td>
			<td>W6500</td>
			<td>Solvent preparation for LC-MS/MS</td>
		</tr>
		<tr>
			<td>Xcalibur Software</td>
			<td>Thermo</td>
			<td>Version 3.0.63</td>
			<td>Data acquisition and interpretation software for LC-MS/MS</td>
		</tr>
	</tbody>
</table>

liquid chromatography coupled to refractive index or mass spectrometric detection for metabolite profiling in lysate-based cell-free systems

Engineering cellular metabolism for targeted biosynthesis can require extensive design-build-test-learn (DBTL) cycles as the engineer works around the cell&#39;s survival requirements. Alternatively, carrying out DBTL cycles in cell-free environments can accelerate this process and alleviate concerns with host compatibility. A promising approach to cell-free metabolic engineering (CFME) leverages metabolically active crude cell extracts as platforms for biomanufacturing and for rapidly discovering and prototyping modified proteins and pathways. Realizing these capabilities and optimizing CFME performance requires methods to characterize the metabolome of lysate-based cell-free platforms. That is, analytical tools are necessary for monitoring improvements in targeted metabolite conversions and in elucidating alterations to metabolite flux when manipulating lysate metabolism. Here, metabolite analyses using high-performance liquid chromatography (HPLC) coupled with either optical or mass spectrometric detection were applied to characterize metabolite production and flux in E. coli S30 lysates. Specifically, this report describes the preparation of samples from CFME lysates for HPLC analyses using refractive index detection (RID) to quantify the generation of central metabolic intermediates and by-products in the conversion of low-cost substrates (i.e., glucose) to various high-value products. The analysis of metabolite conversion in CFME reactions fed with 13C-labeled glucose through reversed-phase liquid chromatography coupled to tandem mass spectrometry (MS/MS), a powerful tool for characterizing specific metabolite yields and lysate metabolic flux from starting materials, is also presented. Altogether, applying these analytical methods to CFME lysate metabolism enables the advancement of these systems as alternative platforms for executing faster or novel metabolic engineering tasks.

To quantify the lysate-based cell-free synthesis of common fermentation products from glucose, lysates derived from strains grown in 2xYPTG media were fed 100 &#181;M glucose as a primary carbon source8. Reactions were stopped over a 24 h time course by protein acidification. Filtered supernatants containing pyruvate, succinate, lactate, formate, acetate, and ethanol produced from glucose catabolism were loaded onto the autosampler module of a HPLC system equipped with a RID module. Vials with filtered mixtures of fermentative end-products and glucose at 1.17 &#181;M, 2.34 &#181;M, 4.69 &#181;M, 9.38 &#181;M, 18.75 &#181;M, 37.50 &#181;M, 75 &#181;M, and 150 &#181;M concentrations in S30 buffer were loaded onto the instrument as standards. Analytes were eluted isocratically from an HPLC column to the RID. Peaks for glucose, succinate, lactate, formate, acetate, and ethanol within the 1 to 150 &#181;M range could be resolved by RID. Peak areas for glucose were derived by manual integration from the RID data for time course and standard curve samples. Extracted peak areas for succinate, lactate, formate, acetate, and ethanol were taken from automatically integrated signals. All standard curves (peak area vs. known concentration) had R2 values &#62;0.99 and were linear throughout the range of concentrations used here.
Molar concentrations for all target analytes were calculated from their respective standard curves. Glucose was consumed within the first 3 h of the reaction and mainly fermented to lactate (Figure 2A,B). Ethanol accumulation also significantly occurred within the first 3 h of the reaction and stopped thereafter (Figure 2C). The observation of significant lactate and ethanol production with significant glucose consumption after 3 h was not unprecedented since lactate and ethanol production pathways allow the regeneration of 1 net mol NAD+ from glycolytic NADH required for continued glucose consumption through glycolysis (Figure 1). Lactate and ethanol can thus be considered as the major fermentation end-products in lysate-based cell-free glucose metabolism. Acetate was initially present in the reactions as a component of the S30 buffer and unexpectedly only accumulated due to metabolism after 6 h when glucose consumption had slowed down (Figure 2D). This result suggests that acetate fermentation does not necessarily enable rapid glycolytic flux in earlier time points. Meanwhile, formate and succinate were synthesized as minor fermentation products (Figure 2E,F). Altogether, the method enabled the absolute quantification of sugar substrate depletion and fermentative product formation in E. coli S30 lysates.
MS detection to profile lysate glucose metabolism specifically was applied here. Lysates derived from strains grown in 2xYPTG media were fed 13C6-glucose as a carbon source. CFME reactions were run in triplicate for 0 h, 1 h, 2 h, and 3 h. Samples from each timepoint were loaded on an LC system equipped with a reversed-phase column and coupled to Fourier transform and ion trap mass spectrometers. Negative ion mode spectra were obtained and processed to analyze organic acids, sugar phosphates, and amino acids. Calculated theoretical masses of 13C-labeled species belonging to central carbon metabolism were searched to identify specifically glucose-derived compounds. Based on the utilized source strain cultivation conditions and previous reports of active pathways in E. coli CFME, it is assumed here that the lysate proteome comprises a metabolic network that feeds glucose into glycolytic fermentation, the pentose phosphate pathway, and possibly amino acid anabolism5,6,7,8,14 (Figure 1). Therefore, the search was narrowed down to members of these pathways, of which 16 metabolites incorporating glucose-derived 13C labels were unambiguously annotated (Supplemental Table 1).
13C6-glucose was observably consumed through glycolysis, as evidenced by the fluctuations in glycolytic intermediate abundances (Figure 3A-E). Consistent with the HPLC-RID data, glucose accumulated to 13C3-lactate and was also fermented to 13C3-succinate within the first 3 h of the reaction (Figure 4A,B). The formation of 13C3-succinate isotopologue supports the proposed model of lysate glucose metabolism (Figure 1), where succinate is likely to be generated by the carboxylation of 3-carbon phosphoenolpyruvate (PEP) molecule and not from the entry of a 2-carbon acetyl-CoA molecule to the TCA cycle. Activation of the TCA cycle has been assumed in previous CFME studies, but other 13C-labeled intermediates of TCA were not detected here8,19,21. 13C3-aspartate synthesis however occurred within the first h and was consumed, reinforcing the idea that PEP is directly converted to oxaloacetate (Figure 1, Figure 6C). The data are reflective of a lysate proteome from source strains harvested during fermentative growth on glucose-rich media (2xYPTG). This would further imply that the rest of the TCA enzymes not participating in succinate production form an oxidative TCA branch (Figure 1). None of the metabolites in this pathway, however, were detected, possibly because high concentrations of glutamate added to the CFME reaction as a salt counterion prevent the progression of this branch. 
The HPLC-RID data is additionally complemented by the lack of 13C2-acetate detection within the 3 h reaction timeframe suggesting no build-up of acetate from glucose up to 3 h (Figure 2B). However, the direct precursor of acetate, acetyl-phosphate (acetyl-P), accumulated, suggesting that the Pta arm of the Pta-AckA pathway for acetate synthesis from acetyl-CoA is active (Figure 4C,D). The AckA catalyzed dephosphorylation of 13C2-acetyl-P to 13C2-acetate likely does not occur within this timeframe due to acetate being a major component of the S30 buffer used in the reactions (Figure 1, Figure 2B).
The incorporation of 13C6-glucose-derived carbons to sugar phosphates 6-phosphogluconolactone (6PGL), 6-phosphogluconate (6PG), ribulose-5-phosphate (Ru5P), and sedoheptulose-7-phosphate (S7P) was also observed (Figure 5). These results confirm the participation of the pentose phosphate pathway in lysate glucose metabolism and likely feeds 13C9-tyrosine synthesis, which has been suggested before by a proteomic study, while also providing a precursor for 13C5-histidine production (Figure 6A,B)7. Labeled phenylalanine and tryptophan were not observed here, and neither were most of the essential amino acids. However, this is not entirely surprising since amino acid anabolism is likely to be enriched in lysates derived from cells grown in nutrient-starved conditions or at the stationary phase7,22. Moreover, the data thus far suggests that intermediates of glycolysis and fermentation are funneled towards cofactor regenerating end reactions, which must preclude the synthesis of many amino acids derived from glyceraldehyde-3-phosphate, pyruvate, and acetyl-CoA (i.e., glycine, cysteine, serine, alanine, valine, leucine, and lysine) (Figure 1). As mentioned, 13C3-aspartate was produced within the first hour, whereas aspartate derived 13C-incorporating amino acids (i.e., threonine, isoleucine, methionine, and asparagine) were not observed possibly because glucose-derived aspartate participates in fermentation (Figure 1, Figure 6C). Lastly, flux towards labeled glutamate and amino acids derived from glutamate may have been impeded by high levels of glutamate in the reaction environment (Figure 1).
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/62852/62852fig01.jpg" /> 
Figure 1: A putative metabolic model of lysates derived from E. coli BL21DE3-Star growing exponentially in high glucose concentrations. Intermediates and end-products of glycolysis (green), the pentose phosphate pathway (dark orange), and fermentative pathways (blue) from acetyl-CoA have been reported in lysate-based CFME. The presence of succinate fermentation implies the activation of the oxidative TCA branch (gray). Amino acid anabolism (gold) in lysates is not well-defined and is investigated here. <a href="https://www.jove.com/files/ftp_upload/62852/62852fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/62852/62852fig02.jpg" /> 
Figure 2: HPLC-RID data for glucose consumption and fermentative end-product synthesis in CFME reactions prepared with E. coli crude extracts. (A) Glucose consumption and (B) lactate, (C) ethanol, (D) acetate, (E) formate, and (F) succinate production in CFME reactions were monitored over 24 h. Average mM concentrations and error bars (SE) quantified with standard curves are presented (n = 3). <a href="https://www.jove.com/files/ftp_upload/62852/62852fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/62852/62852fig03.jpg" /> 
Figure 3: Time course trends of 13C6-glucose and 13C-labeled glycolytic intermediates in E. coli lysate&#160;CFME. Relative abundances of&#160;(A) 13C6-glucose, (B) 13C6-glucose-6-phosphate/fructose-6-phosphate, (C) 13C6-fructose-1,6-bisphosphate, (D) 13C3-glyceraldehyde-3-phosphate/dihydroxyacetone phosphate, and (E) 13C6-pyruvate in CFME reactions over 3 h. Raw peak areas extracted by mzMINE software were used to calculate averages and error bars (SE) for positive annotations (n = 3). <a href="https://www.jove.com/files/ftp_upload/62852/62852fig03large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/62852/62852fig04.jpg" /> 
Figure 4: Time course trends of intermediates and end-products in 13C6-glucose fermentation in E. coli lysate CFME. Relative abundances of&#160;(A) 13C3-lactate, (B) 13C3-succinate, (C) 13C2-acetyl-phosphate, and (D) 13C2-acetyl-CoA in CFME reactions over 3 h. Raw peak areas extracted by mzMINE software were used to calculate averages and error bars (SE) for positive annotations (n = 3). <a href="https://www.jove.com/files/ftp_upload/62852/62852fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/62852/62852fig05.jpg" /> 
Figure 5: Time course trends of 13C6-glucose derived pentose phosphate pathway intermediates in E. coli lysate CFME. Relative abundances of&#160;(A) 13C6-6-phosphogluconolactone, (B) 13C6-6-phosphogluconate, (C) 13C5-ribulose-5-phosphate, and (D) 13C7-sedoheptulose-7-phosphate over 3 h. Raw peak areas extracted by mzMINE software were used to calculate averages and error bars (SE) for positive annotations (n = 3). <a href="https://www.jove.com/files/ftp_upload/62852/62852fig05large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/62852/62852fig06.jpg" /> 
Figure 6: Time course trends of detected 13C6-glucose derived amino acids in E. coli lysate CFME. Relative abundances of&#160;(A) 13C9-tyrosine, (B) 13C5-histidine, and (C) 13C3-aspartate over 3 h. Raw peak areas extracted by mzMINE software were used to calculate averages and error bars (SE) for positive annotations (n = 3). <a href="https://www.jove.com/files/ftp_upload/62852/62852fig06large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Supplemental Figure 1: Representative HPLC-RID chromatogram showing peaks for major fermentative products in a CFME reaction incubated at 37 &#176;C for 24 h. Glucose, succinate, lactate, formate, acetate, and ethanol peaks are sufficiently distinguishable by their retention times on an HPLC column during isocratic elution with 5 mM sulfuric acid solvent. <a href="https://www.jove.com/files/ftp_upload/62852/JoVE-Suppfig1.eps" target="_blank">Please click here to download this File.</a>
Supplemental Figure 2: Representative mass spectra for 13C-labeled metabolites, specifically (A) lactate,(B) glucose, and (C) 6-phosphogluconate (6PG) in a CFME reaction incubated at 37 &#176;C for 1 h. <a href="https://www.jove.com/files/ftp_upload/62852/JoVE-SuppFig2.eps" target="_blank">Please click here to download this File.</a>
Supplemental Table 1: List of detected 13C-labeled metabolites, retention times (aligned across samples using MZmine), theoretical fully 13C-labeled negative mode m/z values, m/z values of detected features, and calculated mass errors. <a href="https://www.jove.com/files/ftp_upload/62852/Supplemental Table 1.docx" target="_blank">Please click here to download this Table.</a>

Watch this Scientific Journal Video about Liquid Chromatography Coupled to Refractive Index or Mass Spectrometric Detection for Metabolite Profiling in Lysate-based Cell-free Systems at JoVE.com

Liquid Chromatography Coupled to Refractive Index or Mass Spectrometric Detection for Metabolite Profiling in Lysate-based Cell-free Systems

The protocols describe high-performance liquid chromatography methods coupled to refractive index or mass spectrometric detection for studying metabolic reactions in complex lysate-based cell-free systems.

Engineering cellular metabolism for targeted biosynthesis can require extensive design-build-test-learn (DBTL) cycles as the engineer works around the ...

Research

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Bioengineering

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