Edited by: Pablo Ivan Nikel, Novo Nordisk Foundation Center for Biosustainability (DTU Biosustain), Denmark
Reviewed by: Lars M. Blank, RWTH Aachen University, Germany; Dae-Hee Lee, Korea Research Institute of Bioscience and Biotechnology (KRIBB), South Korea
This article was submitted to Synthetic Biology, a section of the journal Frontiers in Bioengineering and Biotechnology
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Targeted proteomics is a mass spectrometry-based protein quantification technique with high sensitivity, accuracy, and reproducibility. As a key component in the multi-omics toolbox of systems biology, targeted liquid chromatography-selected reaction monitoring (LC-SRM) measurements are critical for enzyme and pathway identification and design in metabolic engineering. To fulfill the increasing need for analyzing large sample sets with faster turnaround time in systems biology, high-throughput LC-SRM is greatly needed. Even though nanoflow LC-SRM has better sensitivity, it lacks the speed offered by microflow LC-SRM. Recent advancements in mass spectrometry instrumentation significantly enhance the scan speed and sensitivity of LC-SRM, thereby creating opportunities for applying the high speed of microflow LC-SRM without losing peptide multiplexing power or sacrificing sensitivity. Here, we studied the performance of microflow LC-SRM relative to nanoflow LC-SRM by monitoring 339 peptides representing 132 enzymes in
Liquid chromatography (LC) selected reaction monitoring (SRM, or multiple reaction monitoring – MRM) targeted proteomics is a popular mass spectrometry (MS)-based protein quantification technique (
Here, we performed a systematic comparison of key characteristics of microflow LC-SRM and the conventional nanoflow LC-SRM platforms through a response curve study of 248
Proteins were extracted from the cell pellets using a metabolite, protein, lipid extraction (MPLEx) method (
The protein pellet was resuspended in 100 mM NH4HCO3 containing 8 M urea and protein concentration was measured by a bicinchoninic acid (BCA) assay (Thermo Fisher Scientific, Waltham, MA, United States). Disulfide bonds were reduced by adding dithiothreitol (DTT) to a final concentration of 5 mM and incubating at 60°C for 30 min with constant shaking at 850 rpm. Samples were alkylated with a final concentration of 40 mM iodoacetamide for 1 h at 37°C at 850 rpm. The reaction was then diluted 10-fold with 100 mM NH4HCO3 followed by the addition of CaCl2 to 1 mM final concentration. Sequencing-grade trypsin (Promega, Madison, WI, United States) was added to all protein samples at a 1:50 (w/w) trypsin-to-protein ratio and incubated for 3 h at 37°C. Digested samples were desalted with 1 mL Discovery C18 SPE columns (Supelco, Bellefonte, PA, United States), using the following protocol: 3 mL of methanol was added for conditioning the column followed by 2 mL of 0.1% TFA in H2O. The samples were then loaded onto each column followed by 4 mL of 95:5: H2O:ACN, 0.1% TFA. Samples were eluted with 1 mL 80:20 ACN:H2O, 0.1% TFA. The samples were concentrated down to ∼100 μL using a Speed Vac and a final BCA was performed to determine the peptide concentration.
Targeted peptides were selected for 132 proteins in major pathways of
To evaluate the peptide quality and select the best responsive transitions for each peptide, 500 fmol/μL of heavy peptide mixture was subjected to high-resolution mass spectrometry analysis (e.g., LTQ Velos Orbitrap MS) since the peptide fragmentation patterns from HCD MS/MS on Orbitrap MS is similar to those from CID MS/MS on triple quadrupole MS (
There are two sets of samples. One is individual
For individual
In the response curve study, the response curves of 248 peptides representing 111 proteins were evaluated by spiking heavy isotope labeled peptides in pooled
Microflow LC-SRM analysis utilized a nanoACQUITY H-Class UHPLC® system (Waters Corporation, Milford, MA, United States), while nanoflow LC-SRM analysis utilized a M-Class UHPLC® system (Waters Corporation, Milford, MA, United States). Both are coupled online to a TSQ AltisTM triple quadrupole mass spectrometer (Thermo Fisher Scientific). The microflow LC-SRM’s UHPLC® system was equipped with an ACQUITY UHPLC BEH 1.7 μm C18 column (1,000 μm i.d. × 15 cm), while the nanoflow LC-SRM’s UHPLC® system was equipped with an ACQUITY UHPLC BEH 1.7 μm C18 column (100 μm i.d. × 10 cm). In both systems, the mobile phases were (A) 0.1% formic acid in water and (B) 0.1% formic acid in acetonitrile. The sample loading for microflow LC-SRM is 50 μL of sample (i.e., 25 μg of peptides), while that for nanoflow LC-SRM is 2 μL of sample (i.e., 0.25 μg of peptides). The gradient profile for the microflow LC contained a duty cycle of 32.0 min and a gradient length of 18.9 min (detailed as following, 0.0:90:7, 1.1:90:7, 12.0:90:28, 18.0:90:60, 20.0:90:95, 22.0:90:95, 23.0:90:1, 24.0:90:50, 25.0:90:1, 26.0:90:7, 32.0:90:7, in terms of min:flow-rate-μL/min:%B), while the gradient profile for the nanoflow LC contained a duty cycle of 110.0 min and a gradient length of 78.0 min (detailed as following, 0.0:0.4:1, 1.0:0.6:1, 6.0:0.6:1, 7.0:0.4:1, 9.0:0.4:6, 40.0:0.4:13, 70.0:0.4:22, 80.0:0.4:40, 85.0:0.4:95, 90.0:0.4:95, 91.0:0.5:95, 92.0:0.5:95, 93.0:0.5:50, 94.0:0.5:95, 95.0:0.6:1, 98.0:0.4:1, 110.0:0.4:1, in terms of min:flow-rate-μL/min:%B). Both LC columns were operated with a temperature of 45°C. The TSQ AltisTM triple quadrupole mass spectrometer was operated with ion spray voltages of 4000 ± 100 V and a capillary inlet temperature of 325°C in microflow SRM mode, while it was operated with ion spray voltages of 2100 ± 100 V and a capillary inlet temperature of 350°C in nanoflow SRM mode. In both microflow LC-SRM and nanoflow LC-SRM, tube lens voltages were obtained from automatic tuning and calibration without further optimization. Both Q1 and Q3 were set at unit resolution of 0.7 FWHM and Q2 gas pressure was optimized at 1.5 mTorr. The transitions were scanned with a minimal dwell time of 0.879 msec for microflow SRM and 0.806 msec for nanoflow SRM, respectively.
All the LC-SRM data were imported into the Skyline software and the peak boundaries were manually inspected to ensure correct peak assignment and peak boundaries. The normalized dot product of the light transition peak areas with the heavy transition peak areas (i.e., DotProduct as denoted in Skyline) was calculated by the Skyline software, and it can be used to check whether the transition peak areas in the two label types are in the same ratio to each other determining their spectral similarity.
For individual samples, the total peak area ratios of endogenous light peptides and their corresponding heavy isotope-labeled internal standards were calculated by the Skyline software. The detectability of a spectra was defined by having DotProduct above 0.86 and maximum intensity of light above 1,300. Peptide-peptide correlation within single proteins were evaluated and there were 16 peptides whose abundance profile across 30 samples were significantly different from other peptides in the same proteins. The final 323 peptides were proceeded with final protein abundance rollup by removing those 16 peptides. Specifically, data were log2 transformed, compared to assure no biases (
For response curve study, the response curves of peptides were generated using the heavy-over-light peak area ratios and the heavy peptides concentrations. Similar to the analysis of individual samples, the DotProduct for all the replicates at the LODs and LOQs level need to be above 0.86 while the maximum intensity of heavy above 1,300. The limit of detection (LOD) was determined from the blanks using the average plus three times the standard deviation of the blank signals, while the limit of quantification (LOQ) using the average plus 10 times the standard deviation of the blank signals. Additionally, LOQs also have coefficient variations of less than 20%. The final LOD and LOQ were listed in
The goal of this study was to develop a high-speed platform that can expedite targeted proteomics analysis, thereby increasing the sample analysis throughput for studying biological systems without significantly reducing the sensitivity. Implementation of this high-speed LC-SRM platform can analyze enzymatic digests of
Schematic diagram of the liquid chromatography selected reaction monitoring (LC-SRM) workflow.
The microflow LC-SRM platform utilized a 1 mm i.d. column packed with 1.7 μm C18 particles, with a total run time of 32 min. By comparison, the nanoflow LC-SRM system employed a 100 μm i.d. column packed with the same C18 particles, with a total run time of 110 min, and thus the microflow LC-SRM platform increases the sample analysis throughput by more than 3-fold. The microflow LC-SRM platform can potentially result in analyzing 10,000 more samples than the nanoflow LC-SRM system each year (
Comparison of the microflow LC-SRM and nanoflow LC-SRM platforms. The top figure includes the size of the column, sample loading, total gradient length, and number of samples per day. The bottom figure shows the number of samples run versus the days spent on the analysis in an ideal situation regardless of the instrument down time. In 1 year, the microflow LC-SRM platform can analyze >10000 more samples than the nanoflow LC-SRM platform.
The study monitored the responses of 248 heavy isotope labeled synthetic peptides (
Performance characteristics of the microflow LC-SRM system versus nanoflow LC-SRM system from the response curve study of 248
In order to evaluate the sensitivity of microflow LC-SRM and nanoflow LC-SRM, the LODs and LOQs of 248 peptides were measured. The LODs and LOQs of all the 248 peptides are listed in
In summary, compared to nanoflow LC-SRM, microflow LC-SRM has comparable or slightly lower sensitivity and similar multiplexing power, but much better sample throughput and stability. The main criteria for applying microflow LC-SRM is whether there is enough biological material (i.e., 25–50 μg of peptide digests) to load onto the larger microflow analytical column.
Both microflow LC-SRM and nanoflow LC-SRM were used to analyze a total of 132 enzymes, including 92 in carbohydrate metabolism, 26 in amino acid metabolism, 4 in nucleotide metabolism, 3 in energy metabolism, 4 in biosynthesis of terpenoids and polyketides, 2 in lipid metabolism, and 1 in xenobiotics biodegradation, as listed in
In this study, the samples fed with glucose were grown in either M9 minimal salts medium or MOPS minimal medium, while samples fed with
The stability of peptide retention time across 30 samples in nanoflow LC-SRM is worse than that in microflow LC-SRM (
Central carbon metabolism (
Among the 132 enzymes monitored in this study, 83 of them comprise central carbon metabolism, the β-ketoadipate pathway, and the initial glucose catabolism pathways, as shown in
There are slight differences of enzyme expression levels between glucose-fed samples grown in MOPS medium versus those in M9 medium, and the major variant enzymes between the two conditions are the ones in the TCA, EMP, and PP pathways (see
Volcano plots displaying differential expressed genes in four comparisons presented by microflow LC-SRM results of protein expression level of pathway genes in
Most of the enzymes are not altered significantly when comparing fructose mixed with either glucose or glucose plus gluconate against glucose (
The uptake of glucose and gluconate into the cell are incorporated through the initial glucose catabolism pathways. Glucose can be converted to gluconate in the periplasmic space by quinoprotein glucose dehydrogenase (encoded by the
Boxplot of the relative abundance of enzymes in the initial glucose catabolism pathways of up-taking glucose and gluconate with
Fructose, glucose, and gluconate metabolism eventually converge to pyruvate and then into the TCA cycle, either directly or through acetyl-CoA as intermediate, while carbon from
Boxplot of the relative abundance of enzymes in
In this study, we systematically compared the performance of two LC-SRM platforms, microflow LC-SRM and nanoflow LC-SRM, through monitoring hundreds of targeted peptides in response curve samples as well as individual samples grown in different environmental conditions. The results of this evaluation clearly demonstrated the promise of microflow LC-SRM as a robust protein quantification system biology tool with high sensitivity, high peptide-multiplexing capability, and high sample throughput. Compared to nanoflow LC-SRM, microflow LC-SRM improves the speed by 3-fold, while providing comparable sensitivity over hundreds of peptides. The results of 132 enzymes in
The datasets presented in this study can be found in online repositories. The name of the repository and link can be found below: Panorama Public,
KB-J and YG planned and designed the targeted proteomic studies. GTB, JG, AG, GJB, CJ, JAM, JKM, and KB-J planned and designed the
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer LB declared a past co-authorship with one of the authors GTB to the handling editor.
We thank Jay Fitzgerald at DOE and members of the Agile BioFoundry for helpful discussions.
The Supplementary Material for this article can be found online at: