In vivo quantitative monitoring of subunit stoichiometry for metabolic

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In vivo quantitative monitoring of subunit stoichiometry for metabolic complexes Rashaun Wilson, and Jay J Thelen J. Proteome Res., Just Accepted Manuscript • DOI: 10.1021/acs.jproteome.7b00756 • Publication Date (Web): 27 Mar 2018 Downloaded from http://pubs.acs.org on March 27, 2018

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Journal of Proteome Research

In vivo quantitative monitoring of subunit stoichiometry for metabolic complexes Rashaun S. Wilson† and Jay J. Thelen* Department of Biochemistry, University of Missouri, Christopher S. Bond Life Sciences Center, Columbia, MO 65211

*Corresponding Author Jay J. Thelen University of Missouri-Columbia Department of Biochemistry Christopher S. Bond Life Sciences Center Columbia, Missouri 65211 Telephone: 573 884-1325 Email: [email protected]

†Present Address Rashaun S. Wilson Yale University Department of Psychiatry 300 George St. New Haven, Connecticut 06519

Abbreviations MRM, Multiple Reaction Monitoring; QqQ, triple quadrupole; hetACCase, heteromeric acetylCoA carboxylase; BADC, biotin/lipoyl attachment domain-containing; DAF, days after flowering; LC-MS/MS, liquid chromatography-tandem mass spectrometry

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Journal of Proteome Research 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ABSTRACT Metabolic pathways often employ assemblies of individual enzymes to facilitate substrate channeling to improve thermodynamic efficiency and confer pathway directionality. It is often assumed that subunits to multienzyme complexes are co-regulated and accumulate at fixed levels in vivo, reflecting complex stoichiometry. Such assumptions can be experimentally tested using modern tandem mass spectrometry, and herein we describe such an approach applied towards an important metabolic complex. The committed step of de novo fatty acid synthesis in the plastids of most plants is catalyzed by the multienzyme, heteromeric acetyl-CoA carboxylase (hetACCase). This complex is comprised of four catalytic subunits and a recently-discovered regulatory subunit resembling the biotin carboxyl carrier protein but lacking the biotinylation motif necessary for activity. To better understand this novel form of regulation a targeted tandem mass spectrometry-based assay was developed to absolutely quantify all subunits to the Arabidopsis thaliana hetACCase. After validation against pure, recombinant protein this multiplexed assay was used to quantify hetACCase subunits in siliques at various stages of development. Quantitation provided a developmental profile of hetACCase and BADC protein expression that supports a recently proposed regulatory mechanism for hetACCase and demonstrates a promising application of targeted mass spectrometry for in vivo analysis of protein complexes.

KEYWORDS Acetyl-CoA carboxylase, ACCase, BADC, fatty acid synthesis, AQUATM-MRM, quantitative mass spectrometry


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INTRODUCTION Accurate quantitation of select proteins in complex biological samples is challenging due to the high demand for selectivity without compromising reproducibility and sensitivity. Tandem mass spectrometry-based approaches, most notably selected or multiple reaction monitoring (SRM or MRM) are capable of meeting these criteria while allowing for multiplexed quantitation through simultaneous monitoring of multiple transition ions within a single, liquid chromatographytandem mass spectrometry (LC-MS/MS) analysis. Custom-synthesized, heavy-isotope labeled peptides against a protein of interest, or AQUATM (Absolute QUAntitation) peptides, can be used as internal standards during an SRM or MRM assay to authenticate target specificity and enable absolute quantitation of proteins in vivo 1-2. The heavy label (13C15N) is positioned at the Cterminal lysine or arginine of the tryptic AQUATM peptide, which does not affect the physicochemical properties of the peptide. Therefore, the AQUATM and native peptides co-elute during liquid chromatography separation and also display identical fragmentation patterns. The mass shift of the AQUATM peptide, revealed during MS analysis, allows quantitation of the native peptide in the biological sample. There are several advantages of AQUATM-MRM over antibody-based techniques, especially when quantifying the stoichiometry of subunits within a complex. AQUATM-MRM is more sensitive; in some instances, peptides can be quantified at sub-attomolar levels, enabling detection of low abundance proteins 1. Antibodies displaying poor sensitivity make quantitation of subunits challenging when changes in protein abundance are slight or fall below the limit of detection of the antibody probe. Secondly, AQUATM-MRM displays a higher specificity for the protein of interest compared to immunoblot analyses 3-5. This is important for subunits that have multiple gene paralogs, as observed herein, that may not be discernable with antibodies. Finally,



efficacy of antibody production can be unpredictable, and extensive peptide or protein antigen preparation does not always guarantee adequate antibody sensitivity and specificity. By targeting short sequence tracts (i.e. peptides), AQUATM-MRM allows for quantitative discrimination of isoforms with high sequence similarity. The multiplex capability of this approach enables simultaneous monitoring of multiple peptides in a single analysis, resulting in a higher throughput assay. Immunoblot analysis lacks this multiplexing feature, which can make it difficult to reproducibly monitor changes in multiple subunits of a given complex, especially when replicates and/or treatments become additional variables. Despite its advantages, AQUATM-MRM requires extensive assay development and validation due to the use of peptides as surrogates for intact protein. We highlight here a specific application of AQUATM-MRM technology; to quantify in vivo levels of all known subunits to a metabolic complex under developmental conditions. In prokaryotes and some plants (dicots and non-graminaceous monocots) the committed step of de novo fatty acid biosynthesis is catalyzed by the protein complex hetACCase 6-7. This complex converts acetyl-CoA to malonyl-CoA through an ATP-dependent carboxylation of the covalently-bound cofactor biotin 8-9 (Figure 1). Both the bacterial and plant hetACCase consist of four repeating subunits: α-carboxyltransferase (α-CT), β-carboxyltransferase (β-CT), biotin carboxylase (BC), and biotin carboxyl carrier protein (BCCP) 7. In Arabidopsis, the α-CT 10 and BC 11 are encoded by single nuclear genes, whereas the β-CT is a single plastid-encoded gene 12, and the BCCP is encoded by two nuclear genes 13. A small family of inhibitory proteins was recently identified in plants, which consists of three different isoforms designated BADC1, BADC2, and BADC3 14. BADC proteins resemble BCCPs in size, sequence, and predicted structure, but are not biotinylated. Based upon this observation it was proposed that BADCs are


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negative regulators of hetACCase. As apparent non-functional analogs of BCCP, it is proposed BADC proteins displace functional BCCP thus reducing the number of biotinyl active sites within a holo-ACCase complex (Salie et al., 2016). Such a model places importance on the steady-state, in vivo levels of BCCP and BADC proteins as a means to modulate flux through de novo fatty acid synthesis. Development of an AQUATM-MRM assay to specifically and accurately quantify each subunit, and isoforms therein, in a multiplexed manner has the potential to support this model and determine if genetic and environmental conditions influence the absolute abundance ratio of BCCP:BADC protein and thus modulate complex activity. Previous studies have indicated bell-shaped patterns of transcript expression for the heteromeric ACCase subunits during the maturation phase of seed development 15-16, while seed oil accumulation displays a positive linear profile. Absolute quantitation of ACCase proteins could result in a similar developmental profile, and changes in BADC abundance could provide regulatory insight. The AQUATM-MRM experimental design was selected to monitor stoichiometric changes in both catalytic and regulatory (BADC) subunits to hetACCase by employing quantitative mass spectrometry. We discuss these findings and best practices for development, validation, and implementation of a multiplexed AQUATM-MRM assay for protein quantitation from biological samples. EXPERIMENTAL PROCEDURES AQUATM peptide design Arabidopsis thaliana hetACCase and BADC protein sequences (TAIR accession numbers AT2G38040, ATCG00500, AT5G35360, AT5G16390, AT5G15530, AT3G56130, AT1G52670, and AT3G15690) were each analyzed in silico for ideal tryptic peptides for mass spectrometry quantitation. A list of all possible tryptic peptides was generated for each protein using the



PeptideCutter program from ExPASy Bioinformatics Resource Portal (SIB Swiss Institute of Bioinformatics). Quantifier peptides smaller than eight amino acids, those containing flanking Arg, Lys (within three residues from cleavage site), or containing internal modifiable Cys and Met residues were excluded from the list, except for BADC3 which contained an internal Cys. Peptides were also BLAST searched (NCBI) against the TAIR 10 Arabidopsis thaliana proteome and unique peptides were selected. The list of peptides was then monitored in an unscheduled MRM method using tryptic digest matrices of recombinant protein and Arabidopsis silique and leaf protein extracts. Procedures for protein extraction and preparation for mass spectrometry analysis are listed below. Target precursor and fragment ion chromatograms were extracted using Skyline software. Peptides that produced an adequate signal (normalized level (NL) > 103) were selected for AQUATM peptide synthesis. AQUATM peptide synthesis Custom AQUATM peptide synthesis was performed by Sigma Life Science Custom Products (The Woodlands, TX). Peptides were synthesized at greater than 95%purity. Peptides were shipped in single-use 0.5 nmol lyophilized aliquots. Plant growth Arabidopsis thaliana ecotype Columbia-0 plants were grown under 12 h light at (23°C, 50% humidity, 50 µmol m-2 s-1, white light, fluorescent bulbs). Siliques were collected 7, 9, 11, and 13 d after flowering (DAF) in biological replicate pools of 20. Siliques were flash frozen in liquid nitrogen and stored at -80°C. Protein extraction Plant tissue was homogenized in extraction buffer (0.9 M sucrose, 100 mM Tris-HCl pH 8.0, 10 mM EDTA, 0.4% (v/v) ß-mercaptoethanol) plus one volume of Tris-buffered phenol and


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incubated with agitation at 4°C for 1 h. Samples were centrifuged at 17,000 x g at 4°C for 5 min, and the phenol phase was transferred into a clean polypropylene tube. Samples were backextracted with one volume of extraction buffer plus phenol and incubated with agitation for 5 min. Centrifugation was repeated as described above, and the phenol phase was transferred to five volumes of ice-cold precipitation solution (100 mM ammonium acetate in 100% methanol) to precipitate protein. Samples were vortexed, and protein was precipitated overnight at -80°C. Samples were centrifuged at 4,000 x g at 4°C for 10 min and supernatant decanted. Pellet was washed twice with precipitation solution, twice with 80% (v/v) acetone in water, and once with 70% (v/v) ethanol in water with centrifugation at 4,000 x g at 4°C for 10 min between each wash. Protein precipitate was stored at -80°C in 70% (v/v) ethanol prior to resuspension. Preparation of samples for AQUATM-MRM Protein was dissolved in urea buffer (8 M urea, 50 mM Tris-HCl, pH 8.0) and quantified using the Bradford method with bovine gamma globulin (BGG) as a protein standard (BioRad Laboratories, Hercules, CA). Protein was portioned into 20 µg aliquots and reduced with DTT at a final concentration of 10 mM for 1 h at 37°C. Samples were then alkylated with iodoacetamide (IAA) at a final concentration of 50 mM and incubated at 25°C in the dark for 1 h. Urea was diluted with 3 volumes of a solution of 10 mM ammonium bicarbonate and 10 mM DTT. Trypsin was added at a 1:50 ratio (trypsin:protein) and incubated at 37°C for 16 h. Tryptic peptides were lyophilized via centrifugal evaporator and stored at -80°C prior to mass spectrometry analysis. Retention time acquisition, transition ion selection, and collision energy optimization AQUATM peptides were resuspended in 0.1% (v/v) formic acid to a final concentration of 5 pmol/µL. Initial assessment of peptides was performed to acquire peptide retention times and



select the top eight most intense transition ions from each precursor peptide based on peak area intensity. A scheduled collision energy method was used to optimize transition ion collision energies for each precursor ion by varying the collision energy and monitoring the resulting transition ion peak area intensity response. Optimized collision energy values were imported into a final, optimized MRM method and are listed in Table S1. AQUATM peptide dilution series A six-point, ten-fold AQUATM peptide dilution series was performed in Arabidopsis thaliana silique tryptic peptide matrix and subjected to multiplexed LC-MS/MS analysis. Analytical standards were doped into 1 µg of silique peptide extract to account for any biological matrix effects (e.g. ion suppression) that could occur during mass spectrometry analysis. The dilution series was run sequentially in biological quadruplicate from 0.01-1000 fmol AQUATM peptide/injection. For all peptides, relative standard deviation (RSD) was below 8% to be considered within the linear range of detection. Recombinant protein expression and SDS PAGE Genes were PCR amplified from Arabidopsis thaliana cDNA and subcloned into a pET28a 6XHis-Tag expression vector (Novagen, Darmstadt, Germany). Recombinant constructs were transformed into E.coli strain BL21 cells. Protein was expressed and purified as previously described using Ni-NTA affinity chromatography under native conditions 17. Purified protein was quantified using the Bradford method with bovine gamma globulin (BGG) as a protein standard (BioRad Laboratories, Hercules, CA), subjected to SDS PAGE (12% (w/v) acrylamide) and stained with Coomassie Brilliant Blue (CBB) to confirm protein expression. Band volume from densitometry scanning of CBB-stained gels was quantified using ImageQuant TL software v. 8.1 (GE Healthcare Life Sciences, Pittsburgh, PA) to assess protein purity (Table S2).


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AQUATM-MRM analysis of recombinant protein linear response Recombinant peptides were resuspended in 0.1% (v/v) formic acid in water to a final concentration of 0.4 µg/µL. A six-point, two-fold recombinant protein dilution series was performed in 1 µg Ricinus communis seed tryptic peptide matrix. The dilution series was run sequentially in biological quadruplicate ranging from 31.3-1000 ng recombinant protein/injection. The AQUATM peptide corresponding to the protein analyzed was loaded at 100 fmol/injection with the exception of BADC3 and β-CT, which were loaded at 1000 fmol/injection. . The recombinant protein linear response was quantified from AQUATM-MRM analysis using the following calculations: 1) Response ratio (Light peak area/Heavy peak area) x fmol AQUATM peptide = fmol recombinant peptide, 2) fmol recombinant peptide x recombinant protein molecular weight (g/mol) = g recombinant protein, and 3) g recombinant protein x (1e9 ng) = ng recombinant protein. The calculated values were plotted in ng on a logarithmic base 2 scale as a function of recombinant protein injected Mass spectrometry analysis Targeted mass spectrometry was performed on a TSQ Vantage EMR triple quadrupole instrument (Thermo Scientific, San Jose, CA) interfaced with a nanoLC 1-D plus liquid chromatography system (Eksigent, Framingham, MA). Autosampling, chromatography, and mass spectrometry were performed as previously described 18. Peptides were bound on a C8 Cap Trap (Michrom Bioresources, Inc., Auburn, CA) and eluted over a 12.5 min gradient of 260% solvent B (0.1% (v/v) formic acid in acetonitrile). The total method time was 25 min at a flow rate of 500 nL/min in conserved flow mode. The mass spectrometry parameters were as follows: Experiment Type: SRM, Collision Gas Pressure: 1.5 mTorr, Q1 Peak Width: 0.2 FWHM, Q3 Peak Width: 0.7 FWHM, and Cycle Time: 2 s. The “Use Tuned S-Lens Value”



option was enabled. All analysis was performed with 1 µg of protein digest on column and a 5 µL injection volume. The AQUATM peptides were injected within the linear range of detection, and mass spectrometry analysis was performed using the optimized, multiplexed method in which all peptides were monitored in a given run. Data analysis was performed using Skyline software v. 2.6.0.7176 19. RESULTS AND DISCUSSION The AQUATM-MRM method has been used for absolute protein quantitation in a variety of biological applications including quantitation of post-translational modifications, biomarker assay development, and metabolic engineering strategies 5, 18, 20-23. However, there are no studies demonstrating the use of AQUATM-MRM to ascertain absolute quantities of all cognate subunits to a protein complex in vivo. This is a particularly relevant application of this technology not only for tightly-associated metabolic complexes, of which there are hundreds in a cell, but also the many metabolic pathway enzymes that assemble into comparatively less tightly-associated metabolons 24. Coupled with the multiple, recent large-scale protein-protein interactions studies in animals 25-26, yeast 27, and plants 28 it is clear that accurate, alternative methods for studying complex abundance and stoichiometry are critical. Metabolic protein complexes such as the heteromeric ACCase are often points of regulatory control for pathways. By studying subunit stoichiometry, it is possible to reveal limiting subunits to complexes or conditional changes in subunit stoichiometry, thus providing rational engineering strategies for modulating enzyme activity. Lastly, we outline procedures for AQUATM-MRM peptide design, assay development, and validation when multiple AQUATM peptides are not available for a given protein. AQUATM peptide design and synthesis


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Since MRM utilizes peptides as surrogates for protein quantitation, the choice of quantifier peptides is critical for experimental success. Besides criteria mentioned in the methods section, additional considerations are discussed here. Seven of the eight ACCase subunits analyzed here are nuclear-encoded but chloroplast-localized, therefore peptides within or near the predicted transit peptide of each protein were excluded. Previous spectra from high-resolution Orbitrap analysis of Arabidopsis thaliana seedling proteins were assessed to determine if peptides had previously been identified using mass spectrometry. Of the selected peptides, only DIVELELK (BCCP2) and LNAQLVPKPSEVEALVTEICDSSSIAEFELK (BADC3) were not experimentally identified previously. To confirm these peptides recombinant protein as well as Arabidopsis silique and leaf protein extracts were analyzed by targeted, unscheduled MRM to confirm signal. All of the selected peptides produced a signal from analysis of recombinant proteins. Peptides were synthesized for each selected sequence containing a C-terminal Arg or Lys labeled with stable isotopes (13C15N). Two peptides were selected for each ACCase subunit, except for the BADC isoforms (Table 1), due to the limited number of optimal peptides available in the protein sequences. The selected AQUATM peptides and their relative location within the corresponding ACCase protein, are shown in Figure 2. Notably, each of the chosen BADC peptides contain either an internal Lys or Arg in their sequences. However, in each instance this was acceptable because these tryptic cleavage sites are located on the N-terminal side of Pro. Established protease rules indicate that tryptic cleavage is suppressed when Pro is C-terminal to a Lys or Arg cleavage site 29. Determination of AQUATM peptide retention times, fragmentation patterns, and collision energy



Neat AQUATM peptides were analyzed by unscheduled MRM to determine chromatography retention times and the most abundant fragment ions for each peptide. The top eight most abundant fragment ions (transitions) were selected for each AQUATM peptide, and diagnostic fragmentation patterns produced from the calculated peak area of each transition ion were determined, resulting in a rank assignment for each transition ion (Table S1). The optimal collision energies were determined for each fragment ion using scheduled MRM. A final scheduled MRM method was then created to target each peptide and its selected transition ions, with a two-minute retention time window for each peptide as noted in Table 1. AQUATM peptide linear response To determine the lower limit of quantitation (LLOQ) for each AQUATM peptide and the optimal amount of peptide to add to each sample that is both within the linear range of detection and quantitatively reproducible, a six-point, ten-fold dilution series was performed. Matrix effects often cause changes in AQUATM peptide responses after addition to the biological sample 21, therefore, the AQUATM peptide dilution series was performed in an Arabidopsis thaliana silique peptide matrix to account for any matrix effects that could interfere with quantitative analysis. In each LC-MS/MS analysis, 1 µg silique peptide matrix was injected along with AQUATM peptide ranging from 0.01- 1000 fmol. The resulting peak areas for each peptide were log base 10 transformed and plotted as a function of fmol AQUATM peptide/injection (Figure 3). For each peptide, the retention time, R2 value, line equation, and lower limit of quantitation (LLOQ) was determined (Table 1; Table S2). The LLOQ for all peptides was 1 fmol/injection with the exception of BADC3 and β-CT peptides which both had a LLOQ of 100 fmol/injection. In this analysis, the native peptide response in the Arabidopsis silique matrix was simultaneously monitored. As the silique matrix injected per run was at a fixed concentration in


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each sample, this enabled the use of the native peptide response as a normalizer, which can be used to calculate the response ratio of the AQUATM/native peptides. These response ratios were then log10 transformed and plotted as a function of AQUATM peptide/injection (Figure 4). Unfortunately, not all native peptides for the ACCase subunits produced signal in the Arabidopsis thaliana silique samples (α-CT: DLYTHLTPIQR, β-CT: AMDSFAPGEK, BC: FGNVVHFGER, BCCP1: DIVELQLK, and BCCP2: DIVELELK). A reason for this could be low ionization efficiency for these peptides. These peptides were excluded from quantitative analysis. Determination of assay accuracy using purified recombinant protein Since most of the ACCase subunits only had a single peptide for quantitation it was necessary to test assay accuracy against purified recombinant protein. Recombinant protein was purified by affinity chromatography, and protein purity was determined by scanning densitometry of CBBstained SDS-PAGE gels (Figure 5). A six-point, two-fold dilution series of recombinant protein was performed ranging from 31.25-1000 ng/injection. AQUATM peptides were spiked into the samples at 100 fmol/injection with the exception of the BADC3 peptide, of which 1000 fmol was injected. Amount of recombinant protein injected was corrected based on calculated purity of the recombinant protein. To account for matrix effects but prevent incidental analysis of native Arabidopsis peptides, the recombinant protein dilution series was performed in a Ricinus communis developing seed protein matrix (Figure 6). To verify that no background native or AQUATM signal was present, the Ricinus communis matrix was first analyzed without AQUATM peptide or recombinant protein. The results from this analysis are listed in Table 2. To achieve perfect linear accuracy, the slope of the peptide response within the linear range of detection should be equal to 1. However, none of the peptides showed this response,



indicating accuracy is below the theoretical expectation. This was somewhat expected based upon previous results in the AQUATM-MRM field 32-34. One study compared the accuracy of the AQUATM peptide strategy to protein standard absolute quantification (PSAQ) by quantifying a dilution series of staphylococcal enterotoxin proteins, SEA and TSST-1 added to a urine protein matrix 33. PSAQ is similar to the AQUATM peptide strategy, however, it employs heavy-labeled recombinant protein as an internal standard to control for digestion efficiency 20. In this study, AQUATM analysis revealed a 21% accuracy in the response of an SEA peptide, while PSAQ revealed a higher accuracy of 105%. Similarly, quantitation of a peptide designed against TSST-1 using AQUATM peptide standards and PSAQ displayed accuracies of 4% and 108%, respectively. These results suggest the low accuracies observed in the AQUATM-MRM analysis could be due to digestion efficiency. Interestingly, this study also reported a 37% overestimation of SEA protein with a second AQUATM peptide, which they attributed to either inefficient solubilization of the AQUATM peptides or adsorption of the AQUATM peptides to the polypropylene tube. This could be a possible explanation for the overestimation observed in the recombinant protein responses of β-CT peptide NFISDDTFFVR or BCCP peptides DIVELQLK and DIVELELK, as their chemical characteristics are similar. Other reviews acknowledge that peptide digestion efficiencies are a disadvantage of the AQUATM-MRM technique and suggest using recombinant protein standards to control for this important step 4, 35. While multiple AQUATM peptides per protein is typically performed to assess assay accuracy, in this study only one peptide was available for most of the target proteins. For this reason and to control for digestion efficiency recombinant protein standards were developed and employed to determine assay accuracy. Determination of the recombinant protein linear response provided correction factors for quantitation of protein in biological samples (Table 2).


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AQUATM-MRM analysis of ACCase and BADC proteins in Arabidopsis silique tissue over development Previous studies have demonstrated changes in ACCase transcript expression during seed development, which correlated with oil accumulation profiles in the seed 16. The validated AQUATM-MRM assay for ACCase was utilized to quantify absolute changes in ACCase and BADC protein abundance over a Arabidopsis silique developmental time course. Developing siliques were used for this analysis based on previous studies that demonstrated changes in ACCase gene expression during silique development 15-16. Collectively, the absolute abundance profiles displayed bell-shaped curves over the stages of development for the majority of the ACCase subunits, similar to previous gene expression data 15-16 (Figure 7). The expression profiles for all three BADC proteins remained relatively unchanged during the developmental timepoints. The CT subunits form an α/β subcomplex at a stoichiometry of 1:1 based upon the bacterial structural model for heteromeric ACCase 7, 36. The α/β abundance ratios observed in our assay ranged from 0.2 at early stages of development (7 DAF) to 0.11 at the peak abundance for both subunits (11 DAF). Deviations from the expected 1:1 stoichiometry could be a result of β-CT being the only ACCase subunit encoded in the plastid, complicating coordinated expression and/or degradation. This result is notable because it suggests α-CT could be the ratelimiting subunit of the complex. Additional findings from this analysis indicate that the BCCP1 protein abundance was 2to 4-fold higher than BCCP2 during development. This suggests that BCCP1 is the dominant isoform involved in ACCase activity during seed development, which has been demonstrated previously 37. Based upon the bacterial model, the CT subunits are either in a 1:1 or 1:2



relationship with the BC/BCCP/BADC half complex 9, 36, 38-39. The lower abundance of the CT subunits reported here in vivo suggest either an excess of BC/BCCP/BADC half complex in vivo or a different quaternary relationship between the half reactions in plants. If the quaternary structure between bacteria and plants is conserved, an excess of BC/BCCP/BADC half reaction would suggest competition for the comparatively limited quantities of the CT half reaction. Coupled with the widely-observed transient association of these two half reactions in plants, it is feasible that regulation of the complex may in part be dictated by BCCP to BADC expression levels, as originally proposed by Salie et al., 2016. The BADC competitive inhibition model of hetACCase presents the possibility of BADC incorporation into the hetACCase complex to reduce its overall activity 14. This analysis reveals an overall increase in BADC/BCCP stoichiometric ratio from early to late stages of development. The competitive inhibition model is therefore supported in this analysis because de novo fatty acid synthesis is slowed at later stages of development. This would, in effect, be a sensitive mechanism for coordinated, nuclear regulation of the complex, whereby a slight change in the BADC/BCCP ratio could alter the activity of hetACCase and ultimately, the rate of de novo fatty acid synthesis. Coupled with the higher in vivo levels of β-CT compared to α-CT, as observed here, this would place genetic control of the complex with both α-CT and the ratio of BCCP/BADC expression. Not only would this regulatory mechanism be energetically efficient for the plant, it would also enable a rapid response to external stimuli and varying environmental conditions. Although it is possible only a portion of the total subunits are participating in the complex at a given time, this assay provides a quantitative assessment of potential hetACCase capacity under changing regulatory conditions. CONCLUDING REMARKS


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AQUATM-MRM is a useful mass spectrometry approach for multiplexed, absolute quantitation of proteins in vivo, which has many biological applications. We demonstrate the utility of this technique to ascertain subunit stoichiometry of multienzyme complexes. To apply such an assay, a series of method development and validation steps are required for accuracy and performance. Using these procedures, a multiplexed assay was developed for quantitation of subunits of the hetACCase complex in Arabidopsis thaliana. Although silique tissue and temporal development were the experimental focus of our study, this assay can now be applied to a variety of experimental conditions and tissues for further regulatory elucidation of this complex in wild type, T-DNA knockout, and transgenic plants. Collectively, a quantitative proteomics application for the regulatory study of metabolic complexes was developed, which has potential for future genetic engineering endeavors.

ACKNOWLEDGEMENTS This research was supported by National Science Foundation Plant Genome Research Program grant IOS-1339385. SUPPORTING INFORMATION The following files are available free of charge at ACS website http://pubs.acs.org: Table S1. Peptide fragmentation data, including transition ions and collision energy Table S2. Quantitation data for MRM analyses, recombinant protein quantitation data, and protein abundances within siliques. AUTHOR CONTRIBUTIONS The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript.



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Table 1. Peptide information obtained from MRM analysis of AQUATM peptide dilution series* Protein target

TM

AQUA

Peptides

SEELGQGEAIANNLR DLYTHLTPIQR AMDSFAPGEK β-Carboxyltransferase NFISDDTFFVR FGNVVHFGER Biotin carboxylase ITSYLPSGGPFVR SPAPGEPPFIK BCCP1 DIVELQLK SPGPGEPPFVK BCCP2 DIVELELK BADC1 SASSAPSPSQAKPSSEK BADC2 TSSSSADRPQTLANK BADC3 LNAQLVPKPSEVEALVTEICDSSSIAEFELK α-Carboxyltransferase

2

RT (min)

Line equation

R

12.4-14.4 12.6-13.6 9.6-11.6 16.1-18.1 12.2-14.2 14.6-16.6 12.7-13.7 14.1-16.1 12.4-14.4 14.1-16.1 7.4-9.4 8.4-10.4 17.2-19.2

y=15800x-20900 y=3660x-45100 y=6400x+15400 y=1130x+3850 y=2110x-3350 y=5630x-84200 y=8380x-48800 y=17800x-77300 y=7330x+29000 y=12100x-55600 y=22600x+29500 y=17600x+38400 y=12.4x+2590

0.998 0.998 1 0.998 1 0.997 1 1 1 1 1 1 0.998

LLOQ (fmol/injection) 1 1 1 100 1 1 1 1 1 1 1 1 100

*The protein target name, peptide sequence, chromatographic retention time (RT), R2 value, line equation, and lower limit of quantitation (LLOQ) are listed for each peptide.

Table 2. Peptide information obtained from MRM analysis of recombinant protein dilution series* Protein target α-Carboxyltransferase β-Carboxyltransferase Biotin carboxylase BCCP1 BCCP2 BADC1 BADC2 BADC3

TM

AQUA

Peptides

SEELGQGEAIANNLR DLYTHLTPIQR AMDSFAPGEK NFISDDTFFVR FGNVVHFGER ITSYLPSGGPFVR SPAPGEPPFIK DIVELQLK SPGPGEPPFVK DIVELELK SASSAPSPSQAKPSSEK TSSSSADRPQTLANK LNAQLVPKPSEVEALVTEICDSSSIAEFELK

Slope

R

LLOQ (ng/injection)

0.216± 0.00125 0.0945 ± 0.00275 0.0471±0.000501 2.717±0.0682 0.109±0.00112 0.404±0.00416 0.364±0.00945 3.553±0.137 0.559±0.00492 1.827±0.0614 0.0410±0.00215 0.628±0.00621 0.346±0.0783

1 0.997 1 0.998 1 1 0.998 0.999 1 0.996 0.997 1 0.83

In vivo quantitative monitoring of subunit stoichiometry for metabolic

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