Abstract
Metabolons, multiprotein complexes consisting of sequential enzymes of a metabolic pathway, are proposed to be biosynthetic “hotspots” within the cell. However, experimental demonstration of their presence and functions has remained challenging. We used metabolomics and in situ three-dimensional submicrometer chemical imaging of single cells by gas cluster ion beam secondary ion mass spectrometry (GCIB-SIMS) to directly visualize de novo purine biosynthesis by a multienzyme complex, the purinosome. We found that purinosomes comprise nine enzymes that act synergistically, channeling the pathway intermediates to synthesize purine nucleotides, increasing the pathway flux, and influencing the adenosine monophosphate/guanosine monophosphate ratio. Our work also highlights the application of high-resolution GCIB-SIMS for multiplexed biomolecular analysis at the level of single cells.
De novo purine biosynthesis (DNPB) is a highly conserved, energy-intensive pathway that coordinates with the purine nucleotide salvage process to maintain purine levels to support cellular proliferation, survival, and metabolic adaptation under varying nutritional supply and evolving environmental demands (Fig. 1A) (1). The de novo pathway is carried out by six enzymes in higher organisms, including humans, commencing with phosphoribosyl pyrophosphate (PRPP), which is converted to inosine monophosphate (IMP) in 10 sequential steps (fig. S1A). IMP is the branchpoint intermediate that is converted to either adenosine 5′-monophosphate (AMP) or guanosine 5′-monophosphate (GMP) by four enzymes. By contrast, the free purine bases hypoxanthine, adenine, and guanine can be combined with PRPP to regenerate their respective mononucleotides by the action of salvage enzymes—hypoxanthine guanine phosphoribosyltransferase (HGPRT) and adenine phosphoribosyltransferase (APRT)—in a single step (Fig. 1A) (2–5).
We previously reported the partial colocalization of multiple DNPB enzymes observed as cytosolic punctate structures, heterogeneous in their size, number, and composition, by fluorescence microscopy (2, 6–8). A substantial fraction of these dynamic structures, called purinosomes, show proximity to mitochondria (9), whereas others reside on microtubules and show directed movement toward mitochondria (10). The mitochondria-associated purinosomes are proposed to constitute the active DNPB metabolon, but the dynamic and fragile nature of such multienzyme complexes (purinosomes and all metabolons in general) (11, 12) has impeded their in vitro reconstitution. Moreover, artifacts introduced by transient overexpression and limitations of fluorescence imaging–based methods have made it challenging to determine the complete enzymatic and ancillary protein composition, to elucidate their relative stoichiometry in the complex, and to ascertain the functional state of the enzymes in purinosomes.
With the purinosome as a potential precedent, we sought support for the hypothesis that cellular metabolic pathways might generally organize in space and time to confer different properties on the collective versus the individual enzymes. Although this study is restricted to HeLa cells, we envision the extension of this methodology to a variety of cells in normal and disease states, leading to insights into how the function of metabolic pathways might be altered to sustain cellular processes.
A model to probe the de novo purine biosynthesis pathway
The two alternative routes of purine synthesis, salvage and de novo, were probed by following the incorporation of labeled hypoxanthine or glycine (Gly), respectively, in the intermediates and end nucleotides of the two pathways (Fig. 1A). Upon purine depletion, where purinosome formation has previously been observed, HeLa cells showed significant de novo synthesis, indicated by higher abundance of the DNPB intermediate 5-aminoimidazole-4-carboxamide ribonucleotide (AICAR) (Fig. 1B) as well as [15N]Gly incorporation in the products, AMP and GMP (hereafter AMP/GMP) (Fig. 1C). When cultured in purine-rich (P+) media, the cells instead seemed to only carry out salvage synthesis, quantified by [15N4]hypoxanthine incorporation in AMP/GMP (Fig. 1C). Thus, we used the purine-depleted HeLa cells, which show high DNPB flux, as the model system to probe the metabolic consequence of purinosome formation.
We developed a model to mathematically predict the distribution of isotopic labels that would be expected in the absence of the DNPB metabolon, and then tested the predictions by performing an in vivo isotope incorporation experiment. When cells are grown in isotopically labeled [13C3,15N]Ser (label on backbone and side-chain carbons as well as the backbone amine), labeled carbon and nitrogen can enter into various metabolites within the pathway (Fig. 1D). Cells take up labeled Ser from the media, which is then internalized by mitochondria through the mitochondrial Ser transporter SFXN1 and is acted upon by a suite of enzymes [serine hydroxymethyltransferase 2 (SHMT2) and different isoforms of methylenetetrahydrofolate dehydrogenase/cyclohydrolase (MTHFD)] that constitute the mitochondrial one-carbon metabolism, producing Gly and formate (13, 14). These products exit the mitochondria and are incorporated in different cytosolic pathways, including the DNPB pathway, by the action of the enzymes GART (trifunctional phosphoribosylglycinamide formyltransferase) and ATIC (bifunctional 5-aminoimidazole-4-carboxamide nucleotide formyltransferase/IMP cyclohydroxylase) (Fig. 1D) (15).
We considered a null hypothesis model assuming each of the 10 steps of the pathway, starting with PRPP and leading up to the formation of IMP, to be independent of each other; all the intermediates to be completely equilibrated with their respective cytosolic pools; and a homogeneous distribution of all the enzymes (i.e., no purinosome formation and localization proximal to mitochondria), coenzymes, substrates, and cofactors in the cytosol. The model allows prediction of the isotopomer distribution in DNPB pathway intermediates and end products assuming uniform isotopically labeled Gly (1 – x) and formate (1 – y) incorporation across the pathway (Fig. 1E). If x and (1 – x) are the respective fractions of unlabeled and labeled Gly, and y and (1 – y) are the respective fractions of unlabeled and labeled formate generated from the mitochondrial metabolism of [13C3,15N]Ser, the incorporation of labeled Gly and formate into the DNPB pathway can be mathematically described (Fig. 1E). It follows that the observed isotopomer distribution in DNPB pathway intermediates that show one Gly and one formate incorporation [i.e., phosphoribosyl-N-formylglycinamide (FGAR), phosphoribosyl aminoimidazole succinocarboxamide (SAICAR), and AICAR] can be used to calculate the source Gly (1 – x) and formate (1 – y) isotope enrichment (Fig. 1F), as well as to predict the expected isotopomer distribution in 5-formamidoimidazole-4-carboxamide ribonucleotide (FAICAR) and all the downstream nucleotides (Fig. 1G). [13C3,15N]Ser is particularly useful in generating unique isotopomer species arising from unlabeled and labeled Gly with no overlap between them and allowing for calculation of the newly generated pools of each intermediate and end product (see supplementary materials).
Channeled de novo purine biosynthesis by purinosomes adjacent to mitochondria
Our model describes DNPB as a simple diffusive relay of reactions (Fig. 1E), and the following testable predictions arise from it: (i) IMP and all the downstream nucleotides must have the same isotopomer distribution of +3, +4, and +5 species, because there is no further isotope incorporation after FAICAR formation; and (ii) labeled Gly and formate enrichment in the DNPB intermediates and end nucleotides generated during the course of the experiment should be the same (fig. S1, B and C). To test these predictions, we performed isotopic incorporation experiments to probe the mitochondriadependent generation of isotopically labeled Gly and formate and their incorporation in purines by supplying a limited concentration of [13C3,15N]Ser (30 μM) for 4 hours, followed by high-resolution quantitative liquid chromatography–mass spectrometry (LC/MS) of cellular metabolite extracts (fig. S2, A to C).
In contrast to the prediction, the fractional abundances of the two isotopomers (+3 and +5) in IMP were significantly different from those in AMP and GMP (Fig. 2A and fig. S2F), respectively, signifying that IMP and AMP/GMP have distinct isotopomeric distributions. To understand the source of this difference, using the observed FGAR and SAICAR isotopomer distribution in each independent experiment, we computed the complete isotopomer distribution in IMP as described by the model and compared it with the observed isotopomer distribution for IMP and all the nucleotides downstream of it, namely xanthosine monophosphate (XMP), succinyl-AMP (SAMP), AMP, and GMP (pathway steps shown in fig. S1A). Whereas the observed distribution for IMP and XMP matched the model-predicted isotopomer distribution (Fig. 2B and fig. S2D), AMP, SAMP, and GMP all showed a significantly different isotopomer distribution relative to the prediction (Fig. 2C and fig. S2, E and F). Consequently, IMP and its precursor substrates FGAR and SAICAR appear to have been synthesized from the same cytosolic pool of substrates (Gly and formate) and to have different isotopic enrichment relative to the substrate pool used for AMP and GMP synthesis. Moreover, no pathway intermediates with the isotopic enrichment seen in AMP/GMP were detected.
Next, using the observed isotopomer distribution in AMP and GMP, we computed the percentage isotopic enrichment in the source substrates of the channeled pathway. The newly generated channeled DNPB products, AMP/GMP, had higher isotope enrichment than IMP, synthesized by the unchanneled pathway, with respect to both Gly and formate. The newly synthesized AMP/GMP showed ~10% higher Gly enrichment (Fig. 2D) and 15 to 20% higher formate enrichment relative to IMP (Fig. 2E). We conclude that the synthesis of AMP and GMP is accomplished in a highly channeled manner, preventing pathway intermediates from equilibrating with their bulk cytosolic pools. The higher isotope enrichment in AMP/GMP relative to IMP indicates the physical proximity of an “active” DNPB metabolon or plausible direct association of the enzymes with the mitochondrial metabolite transporters.
To test this explanation, we poisoned cells with mycophenolic acid (MPA), a specific high-affinity inhibitor of IMP dehydrogenase (IMPDH), an enzyme involved in the synthesis of guanine nucleotides (16). IMPDH inhibition is expected to cause accumulation and leakage of IMP from purinosomes, leading to intermixing of IMP produced from the two independent pathways. As expected, treatment of cells with the inhibitor resulted in significant accumulation of IMP (by a factor of ~12) (Fig. 2F) as a result of forced release of IMP synthesized by the channeled purinosomes. Consistent with our hypothesis, upon MPA treatment the observed labeled formate enrichment in AMP and IMP was similar (Fig. 2E and fig. S2I). Likewise, when the concentration of isotope-labeled Ser (120 μM) was increased by a factor of 4, it led to homogeneous spread of labeled formate across the cytosolic volume. Under these conditions, GMP and AMP (synthesized by channeled pathway) and the intermediates XMP and IMP (synthesized by unchanneled pathway) showed similar formate isotope enrichment (fig. S2, C and M).
These observations provide a rationale for the interpretation that the mitochondria-proximal purinosome must represent the “active” DNPB metabolon. This proximity results in the preferential capture of Ser-derived Gly and formate by “active” purinosomes for channeled DNPB, in which the equilibration of the purinosome-synthesized intermediates with their respective bulk cytosolic pools is limited. The detected IMP, on the other hand, must arise from a second diffusive substrate pathway or incomplete purinosomes. Consequently, the “active” DNPB metabolon represents the assembly of nine enzymes localized proximal to mitochondria, capable of catalyzing the conversion of PRPP to AMP and GMP in a sequence of 14 highly channeled steps (Fig. 2G). This may also rationalize the previously reported directed migration of purinosomes along the microtubule to facilitate the access of mitochondrially generated metabolites, Gly, Asp, and formate.
Instead of labeled Ser, when molar equivalents of labeled Gly and formate are supplemented in the media, action of the enzymes MTHFD1 and SHMT1 regenerated cytosolic labeled Ser (17) (fig. S2G).Under these conditions, we still observed channeled AMP/GMP synthesis, as reflected by the similar isotope incorporation in AMP and GMP (Fig. 2, H and I, and fig. S2H). The percentage of Gly incorporation in the end nucleotides AMP/GMP was normalized by the observed Gly enrichment in reduced glutathione to account for the differences in the uptake of Ser and Gly (Fig. 2H and fig. S2H).
Next, we examined whether the channeled DNPB exhibited an increase in the pathway efficiency, a hallmark of metabolons. We estimated the difference in the efficiencies of the DNPB channeled versus unchanneled pathways operating in parallel. The ratio of total newly synthesized AMP and GMP was higher than that of the total IMP produced during our experiment by a factor of ~7, highlighting the effectiveness of the mitochondria-associated multienzyme assembly in achieving greater pathway flux (fig. S2J). The role of mitochondrial metabolism in supporting the channeled pathway was further tested by knocking down the mitochondrial formate production pathway, and consequently 10-formyltetrahydrofolate (10-formyl-THF) production, by targeting MTHFD2 (one of the enzymes involved in mitochondrial one-carbon metabolism) (18) (Fig. 2J). Upon small interfering RNA (siRNA)–mediated knockdown of MTHFD2 (fig. S2K), there was a disruption in the pathway efficiency by a factor of ~100, reflected in the accumulation of the intermediate AICAR and a decrease in the production of the end product (AMP) relative to the control (Fig. 2K).
IMP lies at a branchpoint step, and its partitioning into the two possible downstream nucleotides AMP or GMP presents an intriguing scenario. The kinetic parameters for the individual enzymes and their overall availability are expected to favor guanine nucleotide synthesis over the adenine nucleotide by at least a factor of ~25 (7). On the other hand, the abundance of adenine nucleotides is higher than that of guanine nucleotides by a factor of ~10, and the adenine nucleotide content in the human genome is higher (~30%) than the guanine nucleotide content (~20%) (19). The channeled pathway favors the synthesis of adenine nucleotides over guanine nucleotides (fig. S2L). We hypothesize that cells may achieve preference for adenine nucleotides by regulating the composition of purinosomes to favor the enzymes adenylosuccinate synthetase (ADSS) and bifunctional adenylosuccinate lyase over IMPDH and GMP synthetase, by modulating the orientation of the branchpoint enzymes in the purinosome, or by localizing purinosomes close to the mitochondrial site of Asp production, thus increasing the availability of Asp for ADSS.
Application of high-resolution GCIB-SIMS imaging to probe biochemistry at the single-cell level
Mass spectrometry imaging (MSI) has emerged as a powerful tool to spatially locate the endogenous and exogenous compounds in various biological systems (20–23). We used GCIB-SIMS, which permits high-mass ion detection with low chemical damage, to study the cytoplasmic distribution of intact molecular ions of purine biosynthetic pathway intermediates and end nucleotides in a frozen hydrated monolayer of HeLa cells (fig. S3) (24–28). Cryo–scanning electron microscopy (cryo-SEM) images of frozen hydrated HeLa cells demonstrated that the cell size and morphology remain unperturbed after sample preparation (fig. S5, A to C). For multilayer in situ chemical profiling, we used high-voltage GCIB-SIMS with a (CO2)n+ (n > 10,000) cluster size and a focus spot 1 μm in diameter, generating an array of mass spectra [mass/charge ratio (m/z) 90 to 900] corresponding to each 1 μm×1 μm × ~300 to 400 nm voxel and covering a total lateral field of view of ~256 μm × 256 μm in each layer (Fig. 3, A to D).
The validity of the GCIB-SIMS images was confirmed by monitoring the deprotonated molecular ion [M-H]− of phosphoinositol lipid [PI 38:4, m/z 885.53, known to localize in the cell membrane (29)] (fig. S5G). Next, we confirmed that the cellular metabolites were localized within the cellular boundary and that the lateral and depth distribution of metabolites was also preserved (fig. S5D). The analysis confirmed that the spectrum obtained from each pixel of a lateral layer remained unaffected by the analysis performed on the adjacent pixels. Subsequently, a depth profile through the cell during a continuous layered scan showed that deeper layers remained undisturbed while the upper layers were being analyzed (Fig. 3C).
A GCIB-SIMS scan of cells produces a set of complex mass spectra because the ionizable metabolites yield several ionic species, including the pseudo-molecular ion, salt adducts, and fragment ions; hence, interpretation can be challenging (20, 28) (Fig. 3D and fig. S3). Before further analysis of the purine biosynthetic pathway, unique peaks were identified that primarily constituted the metabolites of interest, with minimum interference from other compounds. The ionization of pure standard compounds, including all purine nucleotides and the intermediates SAICAR and AICAR, were studied to optimize SIMS measurement that would yield intact deprotonated ions as a characteristic ion (fig. S3). Isotope tracer experiments were leveraged to validate the peak assignments by following the incorporation of isotope-labeled hypoxanthine, Ser, and Gly in the cells grown under P+ or P− conditions, respectively (Fig. 3, E to H). Before MSI, cells were supplemented with stable isotope–labeled [15N]Ser/[13C]Gly (+1 Da isotopomer generation via the DNPB pathway) (Fig. 3F) or [15N4]hypoxanthine (+3.988 Da isotopomer generation via purine salvage pathway) (Fig. 3G and fig. S5, H to L). Isotope label incorporation continued for 12 to 14 hours to ensure sufficient enrichment allowing detection of all isotopomers by GCIB-SIMS. The isotope incorporation percentage measured by SIMS was in agreement with that obtained in bulk analysis by high-resolution LC/MS of cell extracts after 12 hours of incorporation (Fig. 3H).
In situ GCIB-SIMS imaging captures the metabolon in action
As estimated from fluorescence imaging, purinosomes are roughly spheroid multiprotein assemblies with a diameter range of 0.2 to 0.9 μm (2), thus making 3D molecular scanning GCIB with a focal diameter of 1 μm particularly suitable to capture active functional purinosomes. The metabolic channeling observed for the DNPB pathway, if arising as a result of active DNPB by purinosomes, would lead to higher local concentration of the pathway intermediates and end nucleotides close to the enzyme complexes acting as biosynthetic hotspots. We exploited this feature to identify and characterize purinosomes. HeLa cells were grown in purine-depleted media and supplemented with [15N]Ser (see supplementary materials for experimental details) for isotope enrichment for 12 to 14 hours before performing MSI. Because of the mitochondria compartment–specific conversion of Ser to Gly, we expected the mitochondria-associated DNPB metabolon to show spatially confined higher concentrations of isotopically labeled intermediates and end-product nucleotides. Bulk metabolomic estimations by LC/MS showed that AICAR is efficiently channeled and accumulates only under limited formyl-THF availability (figs. S5K and S6A). Therefore, the cytoplasmic loci with high concentrations of the 15N-labeled DNPB intermediate AICAR were used as the reporter of the active purinosomes in the flash-frozen HeLa cells.
The total ion spectrum image was used to define the cellular boundary in each layer (Fig. 4A). From the total ion spectrum of cells, the peak corresponding to labeled AICAR (m/z 338.05, Δm/z 0.01) was selected to obtain its spatial distribution in each layer (Fig. 4, B to D). Each layer was analyzed independently, and pixels with less than 30% of the highest intensity per pixel and/or that appeared outside the defined cell boundary were discarded from the analysis. AICAR showed a nonhomogeneous distribution with distinct, isolated higher-concentration voxels (Fig. 4E and fig. S7, A and B), with ≥3 AICAR ions per voxel. This result suggests a higher abundance of AICAR molecules per voxel by a factor of 300 to 1000 relative to the abundance expected for a homogeneous distribution throughout the cellular volume (fig. S6B). We observed an average density of 10 to 30 15N-enriched AICAR pixels per cell (Fig. 4F), although we expect this to be an underestimation of the number of active purinosomes per cell because of technical limitations.
To analyze the chemical composition of the labeled AICAR pixels, we generated cumulative mass spectra of all such pixels in the top two or three layers from all the cells in a single field of view. Next, we analyzed the isotope enrichment of the downstream pathway metabolites AMP, ATP, and GTP. In each layer, [15N]AICAR pixels showed an elevated 15N/12C ratio for the downstream end-product nucleotide ATP relative to random cellular pixels (Fig. 4G and fig. S7, D and F). The higher 15N/12C ratio of ATP in the labeled AICAR pixels was consistently seen in each layer analyzed and across all replicate experiments performed (Fig. 4G, inset, and fig. S7, E and G). This trend confirms that the enrichment observed in P− HeLa cells was a specific signal arising as a result of an active, channeled DNPB pathway.
We suspect that a similar correlation was not observed for the peak corresponding to the molecular ion from GTP because of the contribution of deoxy-GTP to the same peak in the cytosolic signal. Similarly, 15N label enrichment in AMP could not be observed because of low mass resolution, resulting in overlap of the AMP +1 peak with unlabeled IMP and thus interfering with the precise estimation of [15N]AMP. Also, such correlation between labeled AICAR and ATP was not observed in any of the control experiments—namely, ATIC CRISPR knockout HeLa cells (lacking the enzyme to catalyze the conversion of DNPB intermediate AICAR to IMP) (30) (Fig. 4H and fig. S7H), P+ [15N]Ser (cells with no observable DNPB flux) (Figs. 1C and 4H), and P– [13C]Gly (with leaky and inefficient channeled DNPB) (Fig. 4I and fig. S5, H to L). Together, our results are consistent with the hypothesis that purine production is localized to biosynthetic “hotspots” congruent with the “active” purinosome metabolon within the cell. GCIB-SIMS allows selective identification and analysis of the mitochondria-associated active purinosomes and shows that the levels of the isotopically labeled metabolites AICAR and ATP are statistically above those of the purinosome’s surroundings.
We have shown that the DNPB pathway is carried out by a metabolon that consists of at least nine enzymes that act synergistically to increase the pathway flux by a factor of ~7 and to preferentially partition a key intermediate, IMP, into AMP by a factor of 3 to 4 over GMP. On the basis of our findings, we propose a functional definition of the purinosomes as the “active” DNPB metabolon, located proximal to the mitochondria (Fig. 2G). We envision that a better understanding of the importance of the purinosome metabolon for human health and its role in aggressive cancers with high purine demand may reveal therapeutically important metabolic vulnerabilities. Our work demonstrates the application of mass spectrometry–based techniques to investigate and quantify metabolic channeling in pathways where enzyme coclustering has been observed (31) and highlights the usefulness of high-energy GCIB-SIMS imaging to explore single-cell biochemistry.
Supplementary Material
ACKNOWLEDGMENTS
HeLa ATIC CRISPR-CAS9 knockout cells were a gift from the Zikanova lab, Charles University and General University Hospital, Prague, Czech Republic. V.P. and S.J.B. thank A. Patterson and P. Smith (Huck Institutes of Life Sciences, Penn State) for running LC/MS. H.T. and V.P. acknowledge technical assistance from P. Blenkinsopp and E. Mengusoglu (Ionoptika, UK) for image processing and single-pixel analysis. V.P. thanks S.J.B.’s lab members A. M. Pedley and L.-N. Zou for very useful discussions and inputs.
Funding: Supported by NIH grant GM024129 (S.J.B.), the Huck Institutes of Life Sciences (V.P.), and the Materials Research Institute and the Institutes of Energy and the Environment at Penn State (H.T.).
Footnotes
Competing interests: The authors declare no conflict of interest.
Data and materials availability: The extracted peak areas for the metabolites analyzed in this study can be found in the accessory files. The GCIB-SIMS imaging data are available from Penn State ScholarSphere (32).
SUPPLEMENTARY MATERIALS
science.sciencemag.org/content/368/6488/283/suppl/DC1 Materials and Methods
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