Dysregulation of polyamine homeostasis strongly associates with human diseases. ATP13A2, which is mutated in juvenile-onset Parkinson’s disease and autosomal recessive spastic paraplegia 78, is a transporter with a critical role in balancing the polyamine concentration between the lysosome and the cytosol. Here, to better understand human ATP13A2-mediated polyamine transport, we use single-particle cryo-electron microscopy to solve high-resolution structures of human ATP13A2 in six intermediate states, including the putative E2 structure for the P5 subfamily of the P-type ATPases. These structures comprise a nearly complete conformational cycle spanning the polyamine transport process and capture multiple substrate binding sites distributed along the transmembrane regions, suggesting a potential polyamine transport pathway. Integration of high-resolution structures, biochemical assays, and molecular dynamics simulations allows us to obtain a better understanding of the structural basis of how hATP13A2 transports polyamines, providing a mechanistic framework for ATP13A2-related diseases. ATP13A2 is a lysosomal polyamine transporter, mutated in several diseases including juvenile-onset Parkinson’s disease. Here, the authors report structures of human ATP13A2 in six distinct intermediate states, illustrating most of its conformational cycle. Polyamine homeostasis is essential for cellular viability and cell growth4, and relies on two major systems: the metabolic system, which regulates the generation and degradation of polyamines, and the transport system, which determines cellular polyamine distribution5. Accurate regulation of polyamine homeostasis in human cells is necessary to maintain cellular fitness6.Ubiquitously distributed polyamines are essential for many biological processes, including cell proliferation, differentiation, neuroprotection, and apoptosis5. The lysosomal transporter ATP13A2 was reported to export polyamines from the lysosome to the cytosol7. Clinically, more than 20 mutations of human ATP13A2 (hATP13A2) have been directly associated with the development of hereditary diseases like Kufor–Rakeb Syndrome  and autosomal recessive spastic paraplegia 78 (SPG78)11. Fibroblasts derived from KRS patients or ATP13A2-deficient cells exhibit abnormal lysosomal behaviors, such as polyamine accumulation, decreased lysosomal membrane stability, lysosomal alkalization, and decreased autophagosome degradation ability13. Conversely, overexpression of hATP13A2 alleviated Parkinson’s disease-related neuron damage caused by the accumulation of toxic α-synuclein proteins15. Together, these findings suggest that ATP13A2 plays a critical role in the polyamine transport system.As an essential compartment in the polyamine transport system, the lysosome plays a critical role in balancing polyamine concentrations between the cytosol and lysosome16 and the P5 ATPases, which are found only in eukaryotic species, can be further divided into type A and B subgroups17. P5A was identified as a transmembrane helix dislocase18, whereas P5B member ATP13A2 functions as a polyamine transporter19. The P-type ATPases transport substrates by coupling ATP hydrolysis with protein phosphorylation states and adopting a series of intermediate states, consisting of E1, E1-ATP, E1P-ADP, E1P, E2P, E2-Pi, and E2, in a process known as the Post-Albers reaction17.The P-type ATPases can be classified into five subfamilies (P1 to P5). The P1, P2, and P3 ATPases are ion pumps; the P4 subfamily comprises lipid flippases;17, the dynamic equilibrium between them makes it challenging to capture the structure of hATP13A2 in a single ATP/ADP-free state. Recently, several intermediate structures of hATP13A2 and its yeast homolog YPK9 were solved using single-particle cryo-electron microscopy (cryo-EM)24. However, the E2 state, a crucial intermediate step for polyamine release, has not yet been captured, and the nominal E1-apo structure recently obtained by introducing two amino acid mutations in the polyamine-binding site22 may not accurately represent the physiological E1 state of ATP13A2. Therefore, the underlying mechanism of hATP13A2-mediated polyamine transport remains elusive.The acquisition of high-resolution structures of hATP13A2 throughout the Post-Albers cycle will be crucial to understanding the mechanism of polyamine transport. Although the E1 and E2 states are the two main conformations of the enzyme25. Phosphatidylinositol 3,5-bisphosphate P2) was also reported to promote the fusion of the lysosome and autophagosome in earlier studies26. Furthermore, the lipids phosphatidic acid and PIP2 can initiate the activity of ATP13A2 through interaction with its N-terminal region27. Positively charged polyamines, the only proven ATP13A2 protein substrates, can interact with phospholipids via electrostatic interactions28. These findings suggest that lipids may actively regulate ATP13A2 transportation of polyamines via a mechanism that remains mysterious.ATP13A2 promotes the fusion of the lysosome and autophagosome at the cellular level by recruiting HDAC6 to deacetylate the cytoskeleton protein contacinHere, we report seven cryo-EM structures of hATP13A2 in six intermediate states, importantly including the putative E2 and E1-like states, thereby providing a nearly complete atomic-level conformational cycle spanning the Post-Albers reaction process. Integration of high-resolution structures, biochemical assays, and molecular dynamics (MD) simulations provide a structural basis for polyamine substrate recruitment, translocation, and release by human ATP13A2, which will facilitate our understanding of the pathogenic mechanism of hATP13A2 in neuron diseases.29. A unique NTD adjacent to the A domain contains three short hydrophobic helices  in a triangular shape embedded in the cytosolic leaflet of the lipid bilayer , which reassemble E1P-like structures with a root mean square deviation (RMSD) of 2.91 Å  or phosphate analogs (BeF3− or AlF4−) were used to stabilize hATP13A2 in the E1-ATP or E1P/E2P intermediate states. In the map obtained after incubation with AMP-PCP , a blob of density was clearly visualized near the KGSPE motif in the N-domain  located among TM1, TM2, TM4a, TM5, and TM6, had a chalk-shaped architecture open to the luminal side where substrates were captured . This observation was further supported by our coarse-grained MD simulations, in which no lipid was found in the area, disproving that the observed density was lipid-derived  form in the absence of polyaminesWe consider the dephosphorylated conformation a putative E2 state, which has never been captured for P5B ATPases. In this E2 structure, we observed a significant movement of the A domain, in which the conserved TGE motif was not clearly visible, probably due to its flexibility  and clustered near the release site in the simulations , depending on substrate concentration.The pumping of polyamines from the luminal side to the cytosolic cavity by ATP hydrolysis temporarily raises the polyamine concentration inside the buffering tank. Polyamines follow the concentration gradient and diffuse to the cytosolic side with a minimal energy cost. The following separation of TM2 and TM4b in the E2 state would make the polyamines in the buffering tank move to the release site for release. Meanwhile, phospholipid molecules within their own monolayer near TM2 and TM4b may help remove the polyamines from hATP3A2 in the E2 state.36. The two recently reported nominal E1 structures (one wild-type21 and one mutant22) present almost identical conformations that are distinct from our E1 structure  were solved at relatively high resolutions (3.2–3.7 Å), whereas the E1-like and putative E2 states were solved at medium resolutions  probably due to the rapid dynamic equilibrium between the E1 and E2 states4− before vitrification22. However, using the same buffer conditions, the structure we captured is very similar to the E2P state (RMSD = 0.82 Å)   gene was cloned into the pCAG vector containing a C-terminus tandem twin Strep-tag by homologous recombination using the primers A13-F, A13-R , frozen in liquid nitrogen, and stored at −80 °C until use. For purification, cells were thawed and gently resuspended in lysis buffer for 2 h containing 50 mM MOPS (pH 7.0), 100 mM KCl, 10% glycerin, 5 mM MgCl2, 1 mM dithiothreitol (DTT), 1% (wt/vol) n-dodecyl-β-d-maltopyranoside , 0.2% (wt/vol) cholesteryl hemisuccinate  with EDTA-free protease inhibitor cocktail (Roche). All subsequent steps were performed at 4 °C. The solubilized fraction was clarified by centrifugation at 51,428×g for 60 min, and it was incubated with Strep-Tactin® Sepharose®  for 1.5 h by rotation. After incubation, the resin was collected and washed with 20 column volumes of wash buffer containing 50 mM MOPS (pH 7.0), 100 mM KCl, 10% glycerin, 5 mM MgCl2, 1 mM DTT, 0.05% (wt/vol) DDM, 0.01% (wt/vol) CHS, 1 mM DTT and 1 mM phenylmethylsulfonyl fluoride (PMSF). Finally, the ATP13A2 was eluted with 50 mM MOPS (pH 7.0), 100 mM KCl, 10% glycerin, 5 mM MgCl2, 0.025% (wt/vol) DDM, 0.005% (wt/vol) CHS, 50 mM biotin. The eluate was concentrated and further purified by size-exclusion chromatography (SEC) on a SuperoseTM 6 Increase column  in a SEC buffer containing 50 mM MOPS (pH 7.0), 100 mM KCl, 5 mM MgCl2, 1 mM DTT, 0.06% digitonin. Peak fractions were collected and concentrated to ~5–10 mg/mL before cryo-EM grid preparation.The hATP13A2 was expressed with the human embryonic kidney (HEK) 293-F cell line using polyethylenimine (PEI)  transient transfection method according to the manufacturer’s instructions. Briefly, just before cell transfection, cells were seeded to give the desired cell density of between 2.0 × 102, 1 mM DTT, 0.03% (wt/vol) DDM, 0.006% (wt/vol) CHS, various concentrations of the SPM were incubated at 37 °C for 10 min. The reactions were then mixed with 42 μL of matrix reagent for 10 min at 37 °C and terminated by adding 10 μL of reagent buffer. The supernatant was taken to measure the Pi content after centrifuging at 1200×g for 10 min. Transfer 30 μL of the supernatant to a 96-well plate and then mix with 100 μL of chromogenic agent for 2 min at room temperature, followed by the addition of 100 μL of Reagent 6 for 5 min. The absorbance was measured at 636 nm using the microplate reader . Nonlinear regression to the Michaelis–Menten equation and statistical analysis was performed using GraphPad Prism version 9.0.0.ATPase activity was assessed using a commercially available kit by measuring the release of inorganic phosphate (Pi) from ATP according to the kit protocol . Briefly, Enzymatic reactions were performed for 10 min (37 °C) in a final volume of 68 μL containing 2 mM ATP. The purified WT or mutants ATP13A2 (0.2–0.5 μg) in buffer containing 50 mM MOPS (pH 7.0), 100 mM KCl, 10 mM MgCl2, 1 mM DTT, 0.03% (wt/vol) DDM and 0.006% (wt/vol) CHS). The diluted proteins were then labeled by dye (RED-tris-NTA) using a Pierce™ BCA Protein Assay Kit (Thermo Fisher Scientific). Next, polyamine solutions were prepared using MST assay buffer and mixed completely with the labeled proteins in various concentrations. The reaction was incubated for 30 min at room temperature in the dark before the samples were analyzed by the Monolith™ NT.115 instrument (NanoTemper Technologies) at 25 °C using the MST data acquisition software according to the manufacturer’s instructions. Data from three independently performed experiments were fitted to the single binding model via the MO. Affinity analysis software version 2.3 (NanoTemper Technologies).hATP13A2 were cloned into a pCAG vector and then transformed into HEK293F to express the His-tagged recombinant proteins. The purified recombinant hATP13A2 proteins were diluted to 200 nM in MST assay buffer (50 mM MOPS (pH 7.0), 100 mM KCl, 10 mM MgCl3, 5 mM ADP; E1P, 10 mM NaF, and 2 mM AlCl3; E2P, 10 mM NaF, and 2 mM BeSO4; E2-Pi, 10 mM NaF, and 2 mM AlCl3, 2 mM SPM; E2, 2 mM SPM. After incubation for 1–2 h on ice, the mixture was centrifuged at 16,000×g for 10 min at 4 °C, then 4 μL aliquots of the ATP13A2 sample were applied to a freshly glow-discharged  Quantifoil R1.2/1.3 300 mesh Au holey carbon grids (Quantifoil). The grids were blotted for 3–4 s, and then plunge-frozen in liquid ethane using Vitrobot Mark IV (Thermo Fischer Scientific) operated at 10 °C and 99% humidity. All grids were then transferred and kept in liquid nitrogen for data collection. For E1-like state ATP13A2 (apo), freshly purified protein samples in SEC buffer were applied immediately.To capture hATP13A2 in different intermediate states, the purified hATP13A2 were mixed with different inhibitors or substrates at the following final concentrations: E1-ATP, 2 mM AMP-PCP; E1P-ADP, 5 mM NaF, 1 mM AlCl43 or EPU software with a defocus range of −0.8 to −1.2 µm. All datasets were collected using image-beam-shift multiple recording model. The total accumulated dose on the specimen was about 50 e-/Å2 with a total exposure time of 8 s. Each micrograph stack contains 32 frames. The number of micrographs collected for each stated grid is described in Supplementary Table The prepared grids were transferred to a Titan Krios G3i microscope (Thermo Fisher Scientific), running at 300 kV and equipped with a Gatan Quantum-LS Energy Filter  and a Gatan K3 Summit direct electron detector in the electron counting mode. Imaging was performed at a nominal magnification of ×81,000, with the super-resolution pixel size at 0.5475 Å each pixel for the E1-like, E1-ATP, E1-ADP nominal E1P, E2P, and E2-Pi state datasets. Dose-fractionated images were recorded at a nominal magnification of ×64,000, with the super-resolution pixel size at 0.54 Å each pixel for the putative E2 state dataset. All movie stacks were collected with the serialEM44 software or patch motion correction (cryoSPARC)33, and the contrast transfer function (CTF) parameters were estimated using CTFFIND445 or patch CTF estimation (cryoSPARC)33. Micrographs were inspected to remove micrographs that were not suitable for image analysis. All subsequent image processing was performed using cryoSPARC. For all datasets, one hundred micrographs were selected to train the Topaz model using a manual curate exposures job in cryoSPARC. Particles were picked by blob picker and extracted with a box of the size of 300 pixels, Fourier-cropped to 100 pixels, and subjected to rounds 2D classification. Selected particles from 2D classification and the 100 micrographs were then trained for the Topaz model using Topaz train in cryoSPARC. Then, particles of all micrographs were picked by Topaz extract using the trained topaz model in cryoSPARC46 and were extracted with a box of 300 pixels for all datasets. All particles were used for 2D classification. After 2D classification, particles were selected for the Ab-initio reconstruction to generate 4 initial maps in cryoSPARC. Subsequently, the particles were classified by multi-rounds of heterogeneous refinement using the four initial models. The final particles selected from heterogeneous refinement were subjected to non-uniform refinement and local and global CTF refinements to yield a final map. The overall resolution of the final map was determined by the 0.143 criteria of the gold-standard Fourier shell correlation (FSC)47. Local resolution estimation was used to determine the local resolution of each map in cryoSPARC.The single-particle analysis procedures of all states are summarized in Supplementary Figs. 48 was used to get the initial model of ATP13A2 for model building. The initial model of ATP13A2 was fitted to the map, and the coordinates relative to the cryo-EM maps were saved in UCSF ChimeraX49. Models for all structures were built after rigid-body fitting of individual domains into the corresponding maps using the initial model and rounds of coordinate adjustment and local refinement in coot50. Model refinement was performed using Phenix 51 with secondary structure restraints and with the refinement resolution limit set to the overall resolution of the map. Structural figures were prepared using UCSF ChimeraX49 and PyMOL (www.pymol.org/). The final refinement statistics are provided in Supplementary Table For all states, Phyre2 online serverx, y, and z dimension, respectively. The temperature was kept constant at 310 K using the Nose–Hoover thermostat with a 1 ps coupling constant, and the pressure at 1.0 bar using the Parrinello–Rahman barostat with a 5 ps time coupling constant. We used a cutoff of 1.2 nm for the van der Waals interactions using a switch function starting at 1.0 nm. The cutoff for the short-range electrostatic interactions was at 1.2 nm and the long-range electrostatic interactions were calculated by means of the particle mesh Ewald decomposition algorithm with a 0.12-nm mesh spacing. A reciprocal grid of 120 × 120 × 120 cells was used with 4th-order B-spline interpolation. We used the CHARMM36m force field52 and prepared the systems using the CHARMM-GUI web interface53. Force field parameters for the phosphorylated Asp513 were the same as previously described54, and force field parameters for SPM were generated using the CHARMM General Force Field55. To investigate the hydration of the SPM substrates in the binding site, we used Gromacs 2019.6 to perform atomistic MD simulations, 200 ns for each, with SPM and protein restrained in the cryo-EM conformations.The all-atom systems of putative E2 and E2P states were embedded into a lipid bilayer with 40% POPE:40% POPC:20% cholesterol and solvated with a 0.1 M NaCl aqueous solution, resulting in ∼285,000 atoms in total for each system. The dimensions of the equilibrated box were 13.5, 13.5, and 14.0 nm in the 56 and Gromacs 2020.3 or 2020.657. The coarse-grained Martini structures of systems were prepared using the martinize.py56. The asymmetric lipid bilayer with compositions, c (cytosolic leaflet) and l , was prepared using the script insane.py58. The c composition consists of 15.2% cholesterol, 19.8% POPC, 32.0% POPE, 23.0% POPA, 3.0% POPS, 3.5% POPI, and 3.5% PIP2 (c16:0/18:1 phosphatidilinositol 3-4 bi-phosphate), and 38.8% cholesterol, 46.2% POPC, and 15.0% POSM in the luminal leaflet (Supplementary Table Coarse-grained (CG) MD simulations of the putative E2 and E2-Pi state were performed in a model lysosomal membrane using the Martini 2.2 force field59. After well equilibrating the systems in the NVT and NPT, production runs were carried out in the NPT ensemble for 10 μs using the Berendsen barostat60. In both simulations of the putative E2 and E2-Pi state, hATP13A2 was restrained in the cryo-EM conformations. For putative E2, the SPM molecule observed in cryo-EM density was included and restrained. While for E2-Pi, to predict the SPM binding sites, the SPM molecules in cryo-EM model were not included in the simulations. Ten independent simulations were performed for each system to collect statistical data. The last 5 μs trajectories were used for their interactions with SPM and the protein. To calculate the average density map, we used the last 2 μs of each trajectory from ten simulations. The lipid density map was analyzed with GROmaps61. The volume analysis of the cytosolic cavities was performed using the Computed Atlas of Surface Topography of proteins (CASTp) method62.In the CG simulation, we maintained a temperature of 310 K with the v-rescale thermostatg for 15 min, and the supernatant was transferred to a new tube for dryness through evaporation with nitrogen. After that, the sample was re-dissolved with 100 μL of Milli-Q water containing 0.1% formic acid, and centrifuged at 16,000×g for 10 min at 4 °C. Finally, the supernatant was saved for LC-MS/MS analysis.To perform the semi-quantitative analysis of the SPM bound by ATP13A2 in different intermediate states, including apo E1-like, E1P-ADP, E2P, and E2-Pi, divided the purified hATP13A2 protein into four equal parts and mixed with the corresponding inhibitor, respectively (Refer to EM sample preparation). After 1 h of incubation on ice, the proteins were subjected to SEC with the SEC buffer containing the corresponding inhibitor, respectively. Peak fractions were collected and quantified by Bicinchoninic acid (BCA) assay (Beyotime Inst). The same amount of protein sample was used to prepare the sample for mass spectrometric semi-quantitative analysis. Briefly, hATP13A2 proteins were extracted with acetonitrile containing 0.1% formic acid with a volume ratio of 1:4. The reaction system was then centrifuged at 16,000×LC-MS/MS analysis was carried out on a Thermo LC-MS Q Exactive-Orbitrap system with a Kinetex 1.7 μm C18 100 Å LC column . Milli-Q water containing 0.1% formic acid (solvent A) and acetonitrile (solvent B) were used as mobile phases, and all solvents used were LC-MS grade. The flow rate was set at 0.2 mL/min. A 100 μL injection volume was used for the analysis. The capillary temperature was set at 320 °C, and aux gas heater temperature was set at 370 °C. The solvent gradient was as follows (solvent B%): 1–1% (0–1.5 min), 1–5% (1.5–4.5 min), 5–100% (4.5-5.5 min), and 100–1% (5.5–7.0 min). The MS data were acquired in positive ions modes.3  in a 1:1 (w/w) ratio at room temperature for 30 min. The reaction was terminated by adding 20 mM ammonium bicarbonate. Run the cross-linker sample on SDS-PAGE to examine the cross-linking reaction. The Coomassie Brilliant Blue stained gel band was excised and digested with trypsin (Promega) for 16 h at 37 °C. The solution was dried out and desalted using a Mono-Spin C18 column . The peptide mixture was analyzed by a customized 30-cm-long pulled-tip analytical column ; the column was then placed in line with an Easy-nLC 1200 nano HPLC (Thermo Scientific) for mass spectrometry analysis. The analytical column temperature was set at 55 °C during the experiments. The mobile phase and elution gradient used for peptide separation were as follows: 0.1% formic acid in water as buffer A and 0.1% formic acid in 80% acetonitrile as buffer B, 0–1 min, 3–6% B; 1–96 min, 6–36% B; 96–107 min, 36–60% B, 107–108 min, 60–100% B, 108–120 min, 100% B.The purified hATP13A2 (1 µg/µL) were cross-linked with BSm/z 355–2000) was acquired, followed by top 20 MS/MS events, sequentially generated on the first to the twentieth most intense ions selected from the full MS spectrum at a 28% normalized collision energy. Full-scan resolution was set to 70,000 with automated gain control (AGC) target of 3e6. MS/MS scan resolution was set to 17,500 with an isolation window of 1.8 m/z and AGC target of 5e6. The number of microscans was one for both MS and MS/MS scans, and the maximum ion injection time was 20 and 50 ms, respectively. The dynamic exclusion settings used were as follows: charge exclusion, 1 and >8; exclude isotopes, on; and exclusion duration, 40 seconds, respectively. MS scan functions and LC solvent gradients were controlled by the Xcalibur data system (Thermo Scientific).Data-dependent MS/MS analysis was performed with a Q Exactive-Orbitrap mass spectrometer (Thermo Scientific). Peptides eluted from the LC column were directly electro-sprayed into the mass spectrometer with the application of a distal 2.5-kV spray voltage. A cycle of one full-scan MS spectrum (3 + SPM(340.2838) . Cysteine alkylation by iodoacetamide was specified as fixed modification and Methionine oxidation, protein N-terminal acetylation as a variable; peptide length, minimum 6 amino acids and maximum 60 amino acids per chain; peptide mass, minimum 600 and maximum 6000 Da per chain; enzyme, trypsin, with up to three missed cleavage sites per cross-link. Protein sequences of ATP13A2 proteins were used for database searching. Precursor and fragment tolerances were 10 and 20 ppm, respectively. The results were filtered by requiring a spectral false identification rate ≤0.01. MS2 spectra were annotated using pLabel63, requiring mass deviation ≤20 ppm.The search parameters used for pLink 2 were as follows: instrument, HCD; precursor mass tolerance, 20 ppm; fragment mass tolerance 20 ppm; cross-linker BSFurther information on research design is available in the Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Movie 1Supplementary Movie 2Reporting Summary


After assessing its environmental state, the cell must rewire its metabolism to support distinct cellular outcomes. Mechanistically, how metabolites regulate cell fate decisions is poorly understood. We used adipogenesis as our model system to ascertain the role of metabolism in differentiation. We isolated adipose tissue stromal vascular fraction cells and profiled metabolites before and after adipogenic differentiation to identify metabolic signatures associated with these distinct cellular states. We found that differentiation alters nucleotide accumulation. Furthermore, inhibition of nucleotide biosynthesis prevented lipid storage within adipocytes and downregulated the expression of lipogenic factors. In contrast to proliferating cells, in which mechanistic target of rapamycin complex 1 is activated by purine accumulation, mechanistic target of rapamycin complex 1 signaling was unaffected by purine levels in differentiating adipocytes. Rather, our data indicated that purines regulate transcriptional activators of adipogenesis, peroxisome proliferator–activated receptor γ and CCAAT/enhancer-binding protein α, to promote differentiation. Although  Adipose tissue is a critical organ in coordinating energy balance, releasing nutrients in times of fasting and storing nutrients in times of nutritional excess. In the context of overnutrition, adipose tissue can expand through adipocyte hypertrophy or through the formation of new adipocytes, termed adipogenesis. Adipogenesis is thought to be a protective and adaptive response to excess nutrients. The transcriptional regulation of adipogenesis is well established , 2. CCAAAdipogenesis is further modulated through post-translational regulatory mechanisms. In response to nutrients, the mechanistic target of rapamycin complex 1 (mTORC1) stimulates adipogenesis . AlthougMuch like transcription and signaling events, metabolites regulate adipocyte differentiation . To induin vivo. Therefore, primary preadipocytes from the stromal vascular fraction (SVF) were stimulated to differentiate for 6 days using a cocktail containing 3-isobutyl-1-methylxanthine (IBMX), dexamethasone, insulin, rosiglitazone, troglitazone, and triiodothyronine (T3) (A). Cell differentiation was confirmed using BODIPY and Oil Red O staining of neutral lipids (A and B). Using mass spectrometry, we compared the steady-state metabolite profiles of undifferentiated and 6 day differentiated primary adipocytes (A). To gain a broad view of the metabolic rewiring that occurs during differentiation, we profiled a total of 218 metabolites and discovered that 117 metabolites were significantly altered. Our analysis confirmed the depletion of amino acids as previously reported (B). Moreover, using MetaboAnalyst 5.0 , we observed that the purine and pyrimidine biosynthetic pathways are the top signatures altered during adipocyte differentiation (C). Because purine metabolism was the pathway most significantly altered during differentiation, we further focused on examining the relative metabolite levels in this pathway (C). Carbamoyl aspartate, 5-aminoimidazole-4-carboxamide ribonucleotide, and inosine monophosphate (IMP), intermediates in the de novo purine synthesis pathway required to produce nucleotides, were depleted . ADP and GDP, which are products of the purine synthesis pathway, were generated, suggesting that the nucleotide biosynthetic pathway is engaged during adipogenesis (D and E and S1C). Urate and allantoin, metabolites in the nucleotide degradation pathway, were similarly enriched in differentiated adipocytes (D and E and S1C). Metabolites in the nucleotide salvage pathway were both enriched and depleted, suggesting that this pathway is also likely active during adipocyte differentiation (D and E and S1C). Altogether, our results reveal major alterations in nucleotide abundance associated with adipocyte differentiation.Transcriptional and signaling programs that regulate adipogenesis are well defined. In addition, recent studies have revealed a critical function of metabolic rewiring to support this process . Howeverine (T3) A. Cell dl lipids , A and Bipocytes A. To gaireported , suggestreported B. Moreovntiation C. Becaus pathway C. Carbamde novo purine synthesis or purine salvage and inhibitors of de novo pyrimidine biosynthesis while inducing differentiation (A and S2A) (de novo purine synthesis enzymes inosine monophosphate dehydrogenase 1 and 2 (IMPDH1 and IIMPDH2) with mizoribine (MIZ) or phosphoribosyl pyrophosphate amidotransferase with 6-mercaptopurine (6MP) resulted in inhibited expression of perilipin and fatty acid binding protein 4 (FABP4), markers of lipid storage and adipocyte differentiation, as measured by Western blot, and decreased lipid accumulation as visualized by Oil Red O and BODIPY in primary adipocytes (B–D and S2B). Of note, 6MP may also inhibit the purine salvage pathway via hypoxanthine–guanine phosphoribosyltransferase 1 and thus may be a more potent inhibitor of adipocyte differentiation. The broader activity of 6MP may explain why this inhibitor exhibits less dose-dependent activity on the expression of adipogenic markers than MIZ (D and E). Inhibition of de novo purine synthesis enzyme phosphoribosylglycinamide formyltransferase with lometrexol (LOM) had no effect on lipid accumulation in primary adipocytes. Inhibition of pyrimidine synthesis enzymes dihydroorotate dehydrogenase (DHODH) with leflunomide or brequinar (BRQ) or thymidylate synthase with 5-fluorouracil (5FU) had a lesser effect on expression of differentiated state markers and lipid accumulation . However, with increasing drug concentrations, BRQ and 5FU produced an inhibitory effect on adipogenic markers (F and G). We next sought to determine whether inhibition of nucleotide biosynthesis also influences differentiation in 3T3-L1 cells, a homogenous preadipocyte population. Blocking purine biosynthesis with LOM, MIZ, or 6MP resulted in a reduced expression of differentiation markers perilipin and FABP4 and decreased lipid accumulation (E–G and S2C). The distinct effects of LOM on lipid accumulation in primary versus 3T3-L1 cells raise the possibility that compensatory mechanisms may counteract the loss of purine biosynthesis in primary cells. To identify whether structurally distinct compounds targeting a single enzyme have comparable effects on lipid accumulation, we examined the effects of IMPDH inhibitors mycophenolic acid (MPA) and AVN944 (AVN). Both MPA and AVN blocked the expression of perilipin and FABP4, mimicking the actions of MIZ (H). As in primary adipocytes, inhibition of pyrimidine biosynthesis had a lesser effect on lipid accumulation during 3T3-L1 differentiation (E–G and S2C). Genetic perturbation of purine synthesis via shRNA-mediated knockdown of IMPDH1 had a similar inhibitory effect on 3T3-L1 differentiation, as evidenced by decreased expression of perilipin and FABP4 and decreased BODIPY staining (H and I). Similarly, the knockdown of DHODH reduced the expression of perilipin and FABP4, supporting the requirement of pyrimidine biosynthesis in differentiating adipocytes (I). Collectively, our results demonstrate that disrupting nucleotide metabolism blocks lipid accumulation in differentiating adipocytes.To determine the function of nucleotide metabolism in differentiating adipocytes from the SVF, we treated cells with inhibitors of ntiation A and S2Aand S2A) , 28. Inhthan MIZ , D and E markers , F and Gs of MIZ H. As in staining , H and Iipocytes I. CollecA). While we observed the previously reported loss of mTORC1 signaling by blocking purine metabolism in HeLa cells (B and C). Moreover, differentiating primary adipocytes or 3T3-L1 cells for 6 days in the presence of purine or pyrimidine metabolism inhibitors did not prevent phosphorylation of mTORC1 substrates S6 or S6K or alter mobility of 4E-BP1 (A and B). These data suggest that the disruption of lipid accumulation observed in adipocytes following inhibition of nucleotide biosynthesis is not dependent on mTORC1 inactivation.mTORC1 exquisitely senses nutrients to regulate cell growth and stimulate anabolic processes such as lipogenesis . As suchFig. S3La cells , 25, prof 4E-BP1 , A and BA). We probed the effect of inhibiting nucleotide biosynthesis on AMPK by measuring its activating phosphorylation at residue T172. Suppression of purine biosynthesis with 6MP and MIZ results in modest AMPK activation as evidenced by increased phosphorylation (B and C). Because AMPK activation blocks lipogenesis , we sought to investigate whether MIZ and 6MP also affected this functional output. We measured de novo lipogenesis by analyzing the incorporation of 14C-glucose into the lipid fraction in the presence of an ACC inhibitor, 5-tetradecyloxy-2-furoic acid and detected decreased incorporation, indicating that the assay is adequate to measure lipogenesis (A). In MIZ- and 6MP-treated SVF cells differentiated for 6 days, de novo lipogenesis is diminished, which is consistent with the decrease in both the transcription and protein expression of enzymes that regulate this process . We noted a similar effect of inhibition of purine biosynthesis on lipogenesis in 3T3-L1 cells differentiated for 6 days (A). AMPK regulates lipid metabolism by directly phosphorylating its substrates, including ACC, HSL, and ATGL . We examined the effects of purine and pyrimidine biosynthesis inhibitors on the phosphorylation state of AMPK substrates. Inhibiting pyrimidine biosynthesis had no significant effect on the phosphorylation state of AMPK substrates . Although 6MP and MIZ activate AMPK, we did not observe an increase in phosphorylation of ACC, HSL, and ATGL . Instead, the expression of these proteins is downregulated by 6MP and MIZ treatment . Given that mTORC1 remains active following the inhibition of purine biosynthesis in adipocytes, we hypothesized that while protein translation may be functioning properly, transcription may be decreased. Moreover, AMPK is a known regulator of SREBP1 . Collectively, our data demonstrate that interfering with purine biosynthesis decreases lipogenesis and final lipid content in differentiating adipocytes. These changes in lipid metabolism may be regulated at the level of transcription.AMPK is another energy and nutrient sensor that regulates lipid metabolism in response to stress  Fig. 4AAFig. 4A.ogenesis A. In MIZr 6 days A. AMPK rf SREBP1 , which pf SREBP1 , 33, 34.Srebp1c and Srebp2 were downregulated transcriptionally by purine biosynthesis inhibitors, we postulated that MIZ and 6MP may modulate early events of transcriptional regulation that promote cell differentiation. If our hypothesis is correct, we would detect a lesser or no effect on lipid accumulation if cells are treated with these compounds after transcriptional initiation. Indeed, treating SVF cells with MIZ and 6MP 4 days after initiation of differentiation had minimal effects on lipid accumulation (A and B), suggesting that interfering with purine biosynthesis may impair early regulatory events that promote adipogenesis. Blocking purine biosynthesis with 6MP and MIZ 2 days after initiation of differentiation effectively inhibited lipid accumulation and expression of adipogenic markers (A and B). To identify the possible factors that may be regulated by inhibition of purine biosynthesis, we profiled transcription factor activation in primary SVF cells stimulated to differentiate into adipocytes over a time course of 6 days (A and B). As established in the literature, C/EBPδ and C/EBPβ are activated early and already expressed in preadipocytes, whereas PPARγ and C/EBPα are stimulated after 1 to 3 days of differentiation (A and B). Blocking purine biosynthesis did not disrupt the activation of transcriptional regulators that are induced after 1 day of differentiation (C) suggesting that CEB/Pδ and C/EBPβ may not be directly regulated by these nucleotides. However, after 2 days of differentiation, expression of PPARγ and C/EBPα was suppressed by both MIZ and 6MP treatment, suggesting that these factors are key transmitters of nucleotide mediation on adipogenesis (C). To evaluate whether restoring key transcriptional regulation is sufficient to prevent adipogenic repression induced by the nucleotide biosynthesis inhibitors, we overexpressed PPARγ2. In the context of PPARγ2 overexpression, MIZ and 5FU failed to block adipogenesis as evidenced by maintained expression of perilipin and FABP4 (D and S5C). Collectively, our data indicate that nucleotide biosynthesis inhibition downregulates transcriptional activators PPARγ and C/EBPα and subsequently blocks adipogenesis.Given that mulation , A and B markers , A and Bf 6 days , A and Bntiation , A and Bntiation C suggestogenesis C. To evand FABP4 D and S5Cde novo purine biosynthesis on adipogenesis may be due to decreased purine availability and thus could be rescued by exogenous nucleoside and nitrogenous bases that can produce nucleotides through the purine salvage pathway. To determine whether adipogenesis can be rescued by the addition of purine nucleosides, we exposed primary SVF cells to adenosine, inosine, and hypoxanthine in the presence of 6MP or MIZ. The addition of nucleosides substantially rescued a 6MP-mediated block in adipogenesis, as assessed by the increased expression of differentiation markers FABP4 and perilipin (A), increased Oil Red O accumulation (B), and increased BODIPY staining (A). MIZ inhibition of adipogenesis was not rescued by adenosine, inosine, and hypoxanthine, as expected, given that MIZ should deplete cellular guanosine and guanine. We next examined whether the addition of nitrogenous bases had the capacity to restore adipogenesis in the presence of purine biosynthesis inhibitors. We observed that adenine addition could rescue the loss of adipogenic markers observed with 6MP (C). Similarly, guanine addition rescued the loss of adipogenic markers and decreased lipid accumulation induced by MIZ (D and S6B). Given that 6MP and MIZ block transcriptional activators of adipogenesis, we next examined whether the addition of nitrogenous bases rescued the expression of PPARγ and C/EBPα (E and F). We noted that adenine and guanine addition restored PPARγ and C/EBPα expression, potentially indicating that purines are sensed to modulate transcriptional programs that regulate cellular outcomes, and limitations in purine availability therefore prevent adipocyte differentiation.We hypothesized that the effects of inhibiting erilipin A, increamulation B, and instaining A. MIZ inwith 6MP C. Similad by MIZ D and S6Bd C/EBPα , E and FIn this study, we sought to elucidate how metabolites regulate adipogenesis using a primary SVF adipocyte cell model. Steady-state metabolomics revealed nucleotide metabolism as the topmost signature altered by differentiation. Inhibition of purine, and to a lesser extent pyrimidine, biosynthesis blocks the transcriptional advancement of adipogenesis, decreasing lipid accumulation in both primary and 3T3-L1 adipocytes. Mechanistically, this regulation does not appear to involve mTORC1, which has previously been shown to sense purines and promote purine biosynthesis in proliferating cells , 25. Impde novo lipogenesis assay confirmed the hypothesis that purine inhibitors block lipogenesis in differentiating adipocytes. Our findings agree with previously published work that demonstrated that 5-aminoimidazole-4-carboxamide ribonucleotide, an activator of AMPK, decreases PPARγ expression and differentiation in 3T3-L1 cells  as required by the Public Health Service Policy on Humane Care and Use of Laboratory Animals. White adipose tissue was dissected and digested in 1 mg/ml collagenase type II  dissolved in 3% bovine serum albumin  in Hanks buffered saline solution with calcium and magnesium for 30 min at 37 °C while shaking at 300 RPM. Dulbecco’s modified Eagle's medium (DMEM) with high glucose and no sodium pyruvate was supplemented with 10% fetal bovine serum (FBS), 10 μM nonessential amino acids , 2 mM glutamine, 20 mM Hepes, and 0.1 μM mercaptoethanol  was used for cell washing and separation through a 100 μm cell strainer. The filtered cell suspension was centrifuged at 600DMEM/nutrient mixture F-12 supplemented with 10% FBS, 1% penicillin and streptomycin, 1.7 μM insulin, 1 μM dexamethasone, and 0.5 mM IBMX was used to induce differentiation. Cells were kept in an induction medium for 2 days and then switched to “maintenance media” consisting of DMEM/nutrient mixture F-12 with 10% FBS, 1% penicillin and streptomycin, 17 nM insulin, 2 μM troglitazone, 1 μM rosiglitazone, and 1 nM T3. Maintenance medium was changed every other day until the end point assays.3T3-L1 preadipocytes were purchased from American Type Culture Collection (CL-173). Cells were cultured in DMEM (Corning) supplemented with 10% FBS (Gibco) and 1% penicillin and streptomycin (Gibco). Once confluent, 3T3-L1 cells were stimulated to differentiate with DMEM containing 10% FBS, 1% penicillin, and streptomycin, and a chemical cocktail of 0.5 mM IBMX, 1 μM dexamethasone, and 1.5 μg/ml insulin. Media were changed every 2 days during the differentiation time course.Cells were treated during the differentiation time course as indicated with 25 μM MIZ , 2 μM LOM , 50 μM 6MP , 1 μM 5FU , 1 μM BRQ , 10 μM leflunomide , 10 μM MPA , or 10 μM AVN , unless indicated otherwise in the figure legends.g for 10 min at 4 °C. Supernatants were immediately dried down in a Vacufuge plus Benchtop Vacuum Concentrator. Dried pellets were stored at −80 °C until they were run on LC–MS.Cells were plated in triplicates for metabolite extraction and in triplicates for cell count normalization. Prior to experiments, cells were differentiated/treated as indicated. For metabolite extraction, cells were washed twice with ice-cold PBS, and polar metabolites were extracted directly on the dish using 1 ml ice-cold LC–MS grade 80:20 methanol:water (Thermo Fisher Scientific). Plates were scraped on dry ice, and lysates were collected in Eppendorf tubes. Lysates were vortexed for 10 min at 4 °C and centrifuged at 16,000m/z = 70 to 1000. The resolution was set at 70,000, the automatic gain control target at 1 × 106, and the maximum injection time was set at 20 ms. An additional scan (m/z = 220–700) was included in negative mode only to enhance the detection of nucleotides.A QExactive bench top orbitrap mass spectrometer equipped with an Ion Max source and a HESI II probe coupled to a Dionex UltiMate 3000 HPLC system (Thermo Fisher Scientific) was used to perform all LC–MS experiments. The instrument underwent mass calibration using the standard calibration mixture every 7 days. About 2 μl of resuspended polar metabolite samples were injected onto a SeQuant ZIC-pHILIC 5 μm 150 × 2.1 mm analytical column equipped with a 2.1 × 20 mm guard column (MilliporeSigma). The column oven was held at 25 °C, and the autosampler tray was held at 4 °C. Buffer A comprised of 20 mM ammonium carbonate and 0.1% ammonium hydroxide. Buffer B was 100% acetonitrile. The chromatographic gradient was run at a flow rate of 0.150 ml/min as follows: 0 to 20 min: linear gradient from 80 to 20% B; 20 to 20.5 min: linear gradient from 20 to 80% B; 20.5 to 28 min: hold at 80% B. The mass spectrometer was operated in full-scan polarity-switching mode, with the spray voltage set to 3.0 kV, the heated capillary at 275 °C, and the HESI probe at 350 °C. The sheath gas flow was 40 units, the auxiliary gas flow was 15 units, and the sweep gas flow was 1 unit. MS data were collected in a range of 2O to remove the excess stain before imaging. Following imaging, Oil Red O stain taken up by lipid droplets was solubilized in 100% isopropanol and quantified by reading absorbance at 492 nm.Accumulation of lipids after 6 days of differentiation was assessed by Oil Red O staining. Oil Red O (Sigma) stock solution was prepared as a 0.3% solution in isopropanol. Cells were washed with PBS, fixed with 4% paraformaldehyde for at least 2 h, washed with 60% isopropanol, and then stained with filtered Oil Red O solution . Cells were washed with dHpBABE puro PPARγ2 plasmid was obtained from Addgene (#8859). shRNAs against IMPDH1 and DHODH were subcloned in the pLKO.1 puro vector (Addgene Plasmid #8453) at EcoRI and AgeI sites. Primer sequences for cloning were used: sh_DHODH:Forward: CCGGCGACGGACTGATCATCACAAACTCGAGTTTGTGATGATCAGTCCGTCGTTTTTG,Reverse: AATTCAAAAACGACGGACTGATCATCACAAACTCGAGTTTGTGATGATCAGTCCGTCG and shIMPDH1_1:Forward: CCGGGATAAGGTGAAGATCGCACAACTCGAGTTGTGCGATCTTCACCTTATCTTTTTG.Reverse: AATTCAAAAAGATAAGGTGAAGATCGCACAACTCGAGTTGTGCGATCTTCACCTTATC shIMPDH1_2:Forward: CCGGCTCCAGAACTAAGTGGTCCATCTCGAGATGGACCACTTAGTTCTGGAGTTTTTG.Reverse: AATTCAAAAACTCCAGAACTAAGTGGTCCATCTCGAGATGGACCACTTAGTTCTGGAG. Subcloning was confirmed with sequencing. Subcloned plasmids were transfected into human embryonic kidney 293T cells with lentiviral packaging vectors. After 48 h, lentivirus was harvested, and target cells were infected in the presence of 10 mg/ml polybrene. Following infection, cells were selected with puromycin.Accumulation of lipids after 6 days of differentiation was measured by BODIPY staining in live cells. Media were replaced with 500 μl DMEM containing 10% FBS and 1% penicillin and streptomycin. BODIPY 493/503 (Cayman) was prepared to a working concentration of 1:500 in DMEM without serum or antibiotics. About 500 μl of this solution was added to the cells and incubated for 30 min at 37 °C. Cells were imaged using a fluorescence microscope .Adherent cells were washed twice with PBS and lysed with radioimmunoprecipitation assay lysis buffer . Protein content was quantified using a Bicinchoninic Acid assay (Thermo Scientific), and equal protein was run on 4 to 20% Tris–Glycine Gels (Invitrogen). Protein was transferred to a nitrocellulose membrane (Bio-Rad). Membranes were incubated with primary antibodies overnight at 4 °C: perilipin , FABP4 , α-tubulin , phospho-S6 240/244 , RPS6 , phospho-p70 Thr389 , p70 49D7 , phospho-Acetyl-CoA Carboxylase , acetyl-CoA carboxylase , phospho-AMPKα , AMPKα , 4EBP1 , p-HSL Ser565 , HSL , ATGL , p-ATGL , C/EBPδ , C/EBPβ , PPARγ , and C/EBPα . Secondary antibodies used were at 1:10,000: IRDye 800CW Donkey Antimouse immunoglobulin G (H + L)  and IRDye 680RD Donkey Anti-Rabbit immunoglobulin G (H + L) . Blots were imaged with the Li-Cor Odyssey CLx infrared imaging system and are representative of at least two independent experiments.RNA was extracted with the Quick-RNA MiniPrep kit (Zymo Research) directly from adherent cells. Complementary DNA was synthesized from 1 μg of RNA using the iScript complementary DNA synthesis kit (Bio-Rad). Real-time quantitative PCR was performed on a Bio-Rad CFX96 using SsoAdvanced Universal SYBR Green SuperMix (Bio-Rad). Mouse quantitative PCR primer sequences used are listed:Fasn: Forward: CAGCAGAGTCTACAGCTACCT and Reverse: AACACCAGAGACCGTTATGC;Scd1: Forward: GAAGTCCACGCTCGATCTCA and Reverse: TGGAGATCTCTTGGAGCATGTG;Acaca: Forward: TGACAGACTGATCGCAGAGAAAG and Reverse: TGGAGAGCCCCACACACA;Hmgcr: Forward: CTTGTGGAATGCCTTGTGATTG and Reverse: AGCCGAAGCAGCACATGAT;Hmgcs: Forward: GCCGTGAACTGGGTCGAA and Reverse: GCATATATAGCAATGTCTCCTGCAA;Srebp1c: Forward: GGAGCCATGGATTGCACATT and Reverse: GGCCCGGGAAGTCACTGT;Srebp1a: Forward: GGCCGAGATGTGCGAACT and Reverse: TTGTTGATGAGCTGGAGCATGT;Srebp2: Forward: GCGTTCTGGAGACCATGGA and Reverse: ACAAAGTTGCTCTGAAAACAAATCA.14C glucose (PerkinElmer) was performed overnight. Cells were washed twice with PBS before lysis in 0.5% Triton X-100. The lipid fraction was extracted by the addition of chloroform and methanol (2:1 v/v). Samples were centrifuged, and 14C incorporation was measured from the lipid-containing phase using a scintillation counter. Each condition was normalized to total cellular protein concentrations and assessed using a Bicinchoninic Acid Protein Assay Kit (ThermoFisher Scientific).For measurement of lipogenesis, cells were starved in no-glucose serum-free media for 24 h. Following starvation, labeling with 1-Details regarding the specific statistical tests, the definition of center, and the number of replicates (n) can be found for each experiment in the figure legends. GraphPad Prism  and MS Excel were used for all quantifications and statistical analyses.Any information required to reanalyze the data reported in this article is available from the lead contact upon request.This article contains The authors declare that they have no conflicts of interest with the contents of this article.


The chemical modification of ribosomal RNA and proteins is critical for ribosome assembly, for protein synthesis and may drive ribosome specialisation in development and disease. However, the inability to accurately visualise these modifications has limited mechanistic understanding of the role of these modifications in ribosome function. Here we report the 2.15 Å resolution cryo-EM reconstruction of the human 40S ribosomal subunit. We directly visualise post-transcriptional modifications within the 18S rRNA and four post-translational modifications of ribosomal proteins. Additionally, we interpret the solvation shells in the core regions of the 40S ribosomal subunit and reveal how potassium and magnesium ions establish both universally conserved and eukaryote-specific coordination to promote the stabilisation and folding of key ribosomal elements. This work provides unprecedented structural details for the human 40S ribosomal subunit that will serve as an important reference for unravelling the functional role of ribosomal RNA modifications. The ribosome is a ribonucleoprotein machine that translates the genetic code in every living organism. It consists of two subunits, comprising 4 ribosomal RNAs (rRNAs) and 80 ribosomal proteins (RPs). The large (60S) subunit is responsible for peptide bond formation, while the small (40S) subunit reads and decodes the messenger RNA (mRNA). Assembly of ribosomal subunits is one of the most energy consuming processes within cells, requiring >300 biogenesis factors and 80 small nucleolar RNAs (snoRNAs) in humans ,2. SimilO-methylation of rRNA ribose and the isomerisation of the nucleoside uridine to pseudouridine ; these chemical modifications are introduced by box C/D and box H/ACA snoRNPs, respectively, with nucleotide specificity dictated by the sequence complementarity of snoRNAs, which pair with the target site . Following stress induction upon addition of 100 mM  NaCl to 250 ml of culture for 20 min, cells were harvested by centrifugation at 800 × g for 10 min. After two consecutive washes with phosphate buffer saline (PBS), cells were harvested by centrifugation, flash frozen in liquid N2 and stored at −80°C. Cells were thawed on ice for 30 min and later resuspended in lysis buffer , 2000 units of RNasin Plus ribonuclease inhibitor (Promega), 0.5 mg/mL heparin and 0.5% Igepal-630 (Sigma)). The slurry was incubated for 30 min on ice with periodic mixing, then centrifuged at 10 000 × g for 5 min at 4°C. The recovered soluble fraction was centrifuged at 30 000 × g for 20 min at 4°C. The resulting supernatant was placed in a separate tube, incubated on ice for 15 min and following the addition of PEG 20 000 to a final concentration of 1.35%, centrifuged at 20 000 × g for 12 min at 4°C. The supernatant was placed in a clean tube and the KCl raised to a final concentration of 130 mM. The solution was incubated for 5 min and cleared by centrifugation at 17 500 × g for 5 min. The concentration of PEG 20000 was raised to 4.25% and the solution incubated for 10 min in ice. After centrifugation at 17 500 × g for 10 min at 4°C the white ribosome-containing pellet was resuspended in 750 μl of buffer R  on ice. 80 OD260 were loaded per 10–30% sucrose gradient, prepared in buffer containing 25 mM HEPES–KOH pH 7.5, 125 mM KCl, 8.3 mM MgCl2, 0.5 mM EDTA, 2 mM DTT. Gradients were centrifuged at 42 800 × g for 15 h at 4°C in an SW28 rotor (Beckman Coulter). Fractions of 1 ml were collected using an AKTA system (Cytiva). Those fractions corresponding to the 80S peak were pooled and precipitated by adding PEG 20000 at a final concentration of 5.15%. The solution was incubated for 10 min at 4°C and centrifuged at 17 500 × g for 10 min at 4°C. The resulting pellet was resuspended in buffer S . 70 OD260 were layered onto a 10–40% sucrose gradient prepared in buffer containing 25 mM HEPES pH 7.5, 550 mM KCl, 5 mM MgCl2 and 2 mM DTT and centrifuged at 70 000 × g for 20.5 h at 4°C in an SW28 rotor (Beckman Coulter). Fractions corresponding to the 40S peak were collected, pooled and 40S subunits precipitated by adding 7.5% of PEG 20000  for 10 min on ice and centrifuging at 17 500 × g for 10 min at 4°C. The final pellet was resuspended in buffer containing 20 mM HEPES–KOH pH7.5, 100 mM KCl, 5 mM MgOAc2 and 1 mM DTT. Aliquots  were flash frozen in liquid N2 and stored at −80°C.To purify human 40S ribosomal subunits, we adapted a previously published protocol used for yeast ribosomes . Human E260/μl) was directly applied onto each grid. The grid was incubated for 30 s at 4 °C and 95% humidity, then blotted for 1 s (blot force −7) prior to plunging into liquid ethane using a Vitrobot Mark IV (FEI Company). Grids were screened for ice quality and cryo-EM data was acquired on a Titan Krios transmission electron microscope (FEI Company) at 300 kV equipped with a K3 direct electron detector (Gatan). The dataset was recorded in counting super-resolution mode at a nominal magnification of 105 000×  with a defocus range of −1.0 to −2.8 μm and a dose of ∼49 e−/Å2. Acquisition of 3091 movies was performed semi-automatically using EPU software (FEI Company) and pre-processed on-the-fly using Warp  for the head domain and 2.09 Å (B-factor: −33 Å2) for the body domain. All resolution estimations are based on the gold-standard Fourier Shell Correlation (FSC) criterion of 0.143 (R2/2 holey carbon supported copper grids (Quantifoil) coated with a 2nm thin carbon layer were functionalised as described . In brieing Warp  to perfolion 3.0  for furtlion 3.0  as impleof 0.143 ,32.2+ and K+, was performed manually in Coot, based on the coordination geometries. Models were refined using real space refinement as implemented in PHENIX , alkylated (iodoacetamide) and subjected to enzymatic digestion with trypsin (Promega) overnight at 37°C. After digestion, the supernatant was pipetted into a sample vial and loaded onto an autosampler for automated LC-MS/MS analysis. The liquid chromatography (LC)–MS/MS experiment was performed using a Dionex Ultimate 3000 RSLC nanoUPLC (Thermo Fisher Scientific) system and a Q Exactive Orbitrap mass spectrometer (Thermo Fisher Scientific). Separation of peptides was performed by reverse-phase chromatography at a flow rate of 300 nl/min and a Thermo Scientific reverse-phase nano Easy-spray column . Peptides were loaded onto a pre-column  from the Ultimate 3000 autosampler with 0.1% formic acid for 3 min at a flow rate of 15 μl/min. After this period, the column valve was switched to allow elution of peptides from the pre-column onto the analytical column. Solvent A was water + 0.1% formic acid and solvent B was 80% acetonitrile, 20% water + 0.1% formic acid. The linear gradient employed was 2–40% B over 90 min . The LC eluant was sprayed into the mass spectrometer by means of an Easy-spray source (Thermo Fisher Scientific Inc.). All m/z values of eluting ions were measured in an Orbitrap mass analyser, set at a resolution of 35 000 and scanned between m/z 380–1500. Data dependent scans (Top 20) were employed to automatically isolate and generate fragment ions by higher energy collisional dissociation (HCD). Normalised collision energy (NCE): 25%) in the HCD collision cell and measurement of the resulting fragment ions was performed in the Orbitrap analyser, set at a resolution of 17 500. Singly charged ions and ions with unassigned charge states were excluded from selection for MS/MS and a dynamic exclusion of 60 s was employed.A sample containing 30 ODP < 0.05 and a peptide cut-off score of 20 were also applied. Scaffold  was used to validate MS/MS based peptide and protein identifications. Peptide identifications were accepted if they could be established at >95.0% probability by the Peptide Prophet algorithm  and searched against a common contaminants database  and the UniProt human database . Variable modifications of oxidation (M), deamidation (NQ) phosphorylation  acetylation (K and protein N-terminus), methylation (HKNR), sulfation (STY) and ubiquitination (K) were applied together with a fixed modification of carbamidomethyl (C). The peptide and fragment mass tolerances were set to 20 ppm and 0.1 Da, respectively. A significance threshold value of lgorithm  with Scalgorithm . ProteinThe small ribosomal subunit consists of two domains, the body and the head Figure . The heaO-methylation (rRNA residues G1447 and A590) , we visualised three of the four proposed pseudouridines , while ψ897 localises to a flexible region where the cryo-EM density could not be interpreted  Figure , C, and ) Figure , Pseudo-) Figure  and SILN) Figure . Of the  Figures . While t Figures . However Figures  and 3A. 6 Figure . Both th+ ions given the composition of the buffers used during sample purification, together with their coordination geometry and distance. Interestingly, compared to the bacterial 30S ribosomal subunit (PDB ID: 6QNR) , a K+ ion nevertheless establishes a similar bonding pattern  , the bin6 Figure . Similarh the K+ . Furthery Figure . An idenbacteria . Human ris bound ,48. Comp2 Figure . Supportd pocket . In our bacteria . For insy Figure . Residue pattern .+ ions bound in eukaryote-specific positions. For example, we identified a K+ ion bound between the peptide backbone of the eukaryote-specific RP eS19 (residue Gly86) and the phosphate backbone of rRNA helices h30 and h42 , which also interacts with two water molecules in square anti-prismatic coordination   adopts a different conformation in eukaryotes  Figure . We iden1 Figure . The evos Figure , likely 1 Figure . By contposition .Our cryo-EM reconstruction revealed the presence of additional density at the N-terminus of two ribosomal proteins, uS2 and eS21 Figure , B. uS2 E. coli ribosome . By contrast, the bacterial isoaspartyl residue (PDB: 7K00) does not interact directly with rRNA, but with Arg35 of the bacterial-specific protein bS21, while the neighbouring residue His118 and Glu31 from bS21 establish π-stacking and hydrogen bonding interactions, respectively, with A718 (https://awi.cuhk.edu.cn/dbPTM/index.php) due to the low local resolution of specific residues  are incorporated (in vivo (7-methylation (Figure 2, RNA modifications are an important source of ribosome heterogeneity that may potentially modulate ribosome function and gene expression during normal development and in cancer ,19,57–66rporated . These m(in vivo , attesti(in vivo ,68,69 (S(in vivo . Howeverm590, Gm1447, ψ572, ψ863 and ψ1136 (Figure Our cryo-EM reconstructions have allowed us to visualise post-transcriptional modifications in unprecedented detail Figure –3. Achie6 Figure . We spec6 Figure ; TK6 andE. coli (Our high-resolution reconstruction allowed us to visualise and propose a role for the N-terminal acetylation on uS2 and eS21 in stabilising interactions with neighbouring residues Figure –D. FurthE. coli . PhylogeE. coli . We specWe have established a pipeline that enables cryo-EM reconstructions of human 40S subunits at resolutions close to 2 Å. We anticipate that this work will pave the way for high-resolution studies of human translation initiation complexes to explore the role of rRNA modifications and ion composition on ribosome function.Coordinates and cryo-EM density maps were deposited in the RCSB Protein Data Bank with accession code PDB 7R4X for the 40S ribosomal subunit model and the Electron Microscopy Database with accession codes EMD-14317, EMD-14318 and EMD-14319 for the entire human 40S, body and head domains, respectively. The mass spectrometric data were deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD031525.gkad194_Supplemental_FilesClick here for additional data file.


Systematic Raman analysis together with high-resolution TEM (HR-TEM) measurements of the tin oxide samples were carried out by changing the calcination temperatures. These data revealed the simultaneous formation of 1D SnO/SnO2 in the rod particles that grew in air. It was also found that Sn(II) can be introduced by changing the concentration of Sn(II) salt in the precursor synthesis and the maximum temperature in calcination. Particles measuring 20~30 nm were sintered to produce tin oxide nanorods including tin monoxide, SnO. Photoabsorption properties associated with the formation of the SnO/SnO2 nanocomposites were also investigated. Tauc plots indicate that the obtained tin oxide samples had a lower bandgap of 2.9~3.0 eV originating from SnO in addition to a higher bandgap of around 3.5~3.7 eV commonly observed for SnO2. Such 1D SnOx/SnO2 hybrids via tin oxalate synthesis with this optical property would benefit new materials design for photoenergy conversion systems, such as photocatalysts. We demonstrate for the first time the structure identification and narrow-bandgap property of 1D hybridized SnO/SnO Liu et al. have recently demonstrated that rich oxygen vacancy can be introduced in SnO2 nanocrystals for applications in visible-light photocatalysts [4 and SnCl2 precursors. Nanocomposites, i.e., ZnO/SnO2−x and SnO2−x/graphene oxide, have also been developed for investigating their photocatalytic activities [2−x, a simple hydrothermal approach using an SnCl2 precursor (SnCl2 dihydrate) was applied to produce SnO2−x, while SnCl2 dihydrate was also utilized in combination with Sn powder for hydrothermal reactions for SnO2−x/graphene oxide. Several tin oxide nanocomposites (SnO/SnO2) have also attracted increasing attention as gas sensors and in battery applications [In recent years, tin oxide nanocomposites  [2 nanoparticle experiments, as illustrated in 2, including photoabsorption that shows a narrowed bandgap (2.9~3.0 eV). Sn(II) can be introduced by the conversion of the precursor under calcination in air when the condition of Sn(II) complexation in polyethylene glycol and the sintering strategy are adjusted. The structure characterization of 1D SnO/SnO2 using HR-TEM measurements and Raman spectroscopy, as well as their photoabsorption properties, will be elucidated.As of now, no reports on the bandgap engineering of 1D-shaped tin oxides are available. This is partially because of the wide-bandgap property of SnO(3.6 eV) . In term2·2H2O), oxalic acid dihydrate, and polyethylene glycol  were purchased from Fujifilm Wako Chemicals, Osaka, Japan and used as received. Ethanol (99.5%) was also purchased from Kanto Chemical Co., Inc., Tokyo, Japan. H2O (resistivity: 18.2 MΩ·cm) was obtained using a Milli-Q® integral water purification system .Tin chloride dihydrate  was performed for 15 min. The supernatant was removed, and the precipitate was centrifuged with water  for 5 min. After the supernatant was discarded, ethanol was added. The precipitation was further treated with centrifugation  for 5 min. The resulting samples were then dried and calcined at 350 °C, 400 °C, 450 °C, 500 °C, and 600 °C in air to produce powder samples. The period of maximum temperature was set to 1.5 h unless otherwise noted. The ramping rate to reach the maximum temperature was 16 °C/min. An electric muffle furnace  was used for the calcination.2.The synthesized powder samples were characterized using X-ray diffraction . Crystallite size of the obtained particles was estimated using the Scherrer equation (D = Kλ/βcosθ), where D, K, λ, and θ indicate crystallite size, Scherrer constant (0.90), X-ray wavelength (1.54 Å), and Bragg angle, respectively. The tin oxide samples were analyzed using XPS . Nanostructures were characterized using SEM  and TEM . Ultraviolet–visible (UV–Vis) spectra were obtained from the diffuse reflectance of the powder samples using a Hitachi U-4000 spectrophotometer. TG-DTA analysis in air flow was carried out using DTG 60H . The ramping rate was 10 °C/min. A confocal Raman microscope, RAMANtouch , was used to analyze the tin oxide samples. The powder samples were irradiated with laser light of 532 nm, and the laser power was adjusted to 5 mW/cm2 and oxalic acid, would affect the decomposition phenomena of the organic parts due to the different oxidation reactions of high valent Sn(IV) sources with increasing temperatures. We changed the concentration of tin chloride and the calcination temperature and time to produce tin oxides while maintaining the 1D morphology of the precursor, as discussed below. Reaction temperatures in the precursor synthesis and amount of tin source were 0 °C, 0.11 g; 60 °C, 0.06 g; 60 °C, 0.22 g; and .The polyethylene glycol (PEG)-template method was applied for synthesizing 1D tin oxalate for conversion into tin oxides. We anticipated that the amount of tin source in the precursor, i.e., the ratio of SnCl2 simultaneously formed for all samples. Taking 2 were detected at 2ϴ = 26.6°, 33.8°, 37.9°, 38.9°, 51.7°, 54.7°, 57.8°, 62.0°, 64.6°, and 65.8°, whereas the peaks at 24.3°, 29.7°, 33.2°, 35.7°, 42.5°, 58.6°, and 63.3° were assigned to the orthorhombic phase. The XRD patterns match well with those of the database.Nucleation control of the precursor compound, tin oxalate, was studied by systematically changing the reaction temperatures and concentrations of tin chloride, as described in the experimental section. Typical SEM images of the synthesized samples are displayed in 2 for all samples. Importantly, the HR-TEM analysis allowed us to understand the SnO phase formation that was not detected in the XRD patterns because of the difficulty of analyzing the major diffraction peaks of SnO that are almost the same as those of orthorhombic SnO2, e.g., at 29.9°  and (101) planes of SnO, respectively. A selected area diffraction (SAD) pattern of the 500 °C sample is depicted in 2, orthorhombic SnO2, and tetragonal SnO). The SAD pattern also indicates the polycrystalline nature of the 1D sample consisting of several primary nanoparticles.The 1D nanostructure formation for the sample in at 29.9° . In termUsing the four samples described in 2 increased with increasing calcination temperatures  in 1.5 h of calcination. Taking the samples in 2, corresponding to (021) planes, increased from 20 nm to 28 nm with longer calcination, suggesting enhanced crystallization in the nanorod formation. As shown in 2 (d = 0.33 nm), orthorhombic SnO2 (d = 0.29 nm), and tetragonal SnO (d = 0.26 nm and 0.30 nm). It should be noted that the formation of SnO in the polymer-directed calcination approach has been evidenced here for the first time by TEM analysis. Apparently, the concentration of tin chloride, the maximum temperature of calcination, and the period of maximum temperature are the key factors that determine nanocomposite formation of 1D SnO/SnO2. A reduced state of Sn(0) or other tin oxide species such as Sn2O3 and Sn3O4 was not detected in our synthesis, suggesting that the SnO was converted directly into SnO2. One of the plausible mechanisms of tin oxides is that the oxidation reaction of Sn(II) hydroxide species in the early stages of calcination (1.5 h) produces SnO as a mixture of SnO/orthorhombic SnO2/tetragonal SnO2.From the XRD data , the est2 during calcination, although they did not isolate the SnO-containing samples in their synthesis. This conversion mechanism from SnO to orthorhombic SnO2 is consistent with our new HR-TEM data of the isolated powder sample presenting the concomitant formation of SnO and orthorhombic SnO2, as shown in The authors of  point ou2 nanoparticles were elucidated not only from absorption spectra but also XPS analysis. Tauc plots of several SnO/SnO2 samples, obtained from diffuse reflectance spectroscopy, are presented in 2 nanoparticles using a single-source precursor approach.The optical properties of the SnO/SnO2 samples calcined at 500 °C for 6 h were also measured. When the reaction temperatures in the precursor synthesis and the amount of tin source were 0 °C and 0.11 g, 60 °C and 0.06 g, 60 °C and 0.22 g, and 60 °C and 0.11 g, respectively, the lower bandgap was estimated to be 2.9~3.0 eV except for the largest amount of tin source (0.06 g). The narrower bandgaps observed in the calcination samples were similar to those of reported SnO bandgaps (2.8–3.0 eV) [The absorption spectra of several SnO/SnO–3.0 eV) . For lon2 nanoparticles, XPS measurements for both the 1.5 and 6 h samples calcined at 500 °C were also performed, as illustrated in 2. For the samples calcinated for 6 h  are assigned to around 110 cm−1 and 208 cm−1, respectively [−1 were clearly observed for all samples and that the intensities were relatively small for the 500 °C and 600 °C samples. The results suggest that SnO oxidation is enhanced for higher calcination times and/or temperatures, as discussed in relation to the XPS data. The vibrational modes of SnO2 were found in the range of 400~800 cm−1, allowing us to characterize SnO and SnO2 nanohybrids in the rod particles. It appears that the laser-induced formation from SnO to Sn2O3 and/or Sn3O4 took place during the Raman measurements [2 in the rod particles.To further prove the hybridization of SnO and SnOectively . We founurements  because 2 nanoparticles with 1D morphology, mainly by systematic Raman analysis and HR-TEM measurement. The calcination temperatures of the tin oxalate precursor were adjusted and 1D SnO/SnO2 were obtained. Sn(II) formation was verified using not only HR-TEM measurements but also Raman and XPS measurements. A lower bandgap of 2.9~3.0 eV corresponding to absorption in the visible light region was estimated from diffuse reflectance spectra. The results of this study provide useful insights into the design of photofunctional tin oxide nanomaterials. One example of this is that this new synthesis can be extended to develop energy materials for visible-light absorbing photocatalysts.For the first time, we have reported the identification of hybridized SnO/SnO


Diabetic ketoacidosis (DKA) was once known to be specific to type-1 diabetes-mellitus (T1D); however, many cases are now seen in patients with type-2 diabetes-mellitus (T2D). Little is known about how this etiology shift affects DKA's outcomes.We studied consecutive index DKA admissions from January 2015 to March 2021. Descriptive analyses were performed based on pre-existing T1D and T2D  and newly diagnosed T1D and T2D .P < 0.001). Patients in all groups were predominantly male except in the PT1D group  (P < 0.001). Most patients were Arabic  except for NT2D, which mainly comprised Asians (53%) (P < 0.001). Patients with NT2D had the longest hospital length of stay (LOS) (6.8 ± 11.3 days) (P < 0.001), longest DKA duration (26.6 ± 21.1 h) (P < 0.001), and more intensive-care unit (ICU) admissions (31.2%) (P < 0.001). Patients with PT1D had the shortest LOS (2.5 ± 3.5 days) (P < 0.001), DKA duration (18.9 ± 4.2 h) (P < 0.001), and lowest ICU admissions (16.6%) (P < 0.001).Of the 922 patients, 480 (52%) had T1D, of which 69% had PT1D and 31% NT1D, whereas 442 (48%) had T2D, of which 60% had PT2D and 40% NT2D. The mean age was highest in PT2D (47.6 ± 13.1 years) and lowest in PT1D (27.3 ± 0.5 years) , showing that T2D is becoming an increasing cause of DKA, with worse clinical outcomes  compared to T1D. Diabetic ketoacidosis (DKA) is one of the most common acute complications of diabetes mellitus (DM). The mortality rates secondary to DKA have significantly improved over time (from around 15% in the 1980s to < 1% in 2020) . The preThe true prevalence of DKA in T2D remains unknown. However, an increasing number of DKA cases are seen in T2D . There aAmid a rising occurrence of DKA admissions among both T1D and T2D, little is known about the effects of both the duration and the type of DM on the clinical course and outcomes of patients with DKA. Newton et al. reported the differences in the DKA population based on duration and type of DM in 176 patients. Although these groups differed in demographics and biochemical results, the authors did not report DKA outcomes in these groups. One notable factor could be the small number of patients in some groups (5 patients in the newly diagnosed T2D group) . In a 15In this study, we aimed to review all patients with index DKA admissions to observe the demographic and clinical differences, as well as differences in the outcomes based on the type and duration of DM among patients presenting with DKA.We retrospectively reviewed all consecutive patients with index DKA admissions from January 2015 to March 2021 in four general hospitals of Hamad Medical Corporation, Qatar.Patients were included according to the following criteria: adult patients (14 years and above) with index DKA admissions within the study period. Patients either had a known DM diagnosis or were newly diagnosed with DM on admission. Hyperglycemia was not used to identify DKA to include euglycemic DKA (EDKA) patients.Patients who did not fulfil the American diabetes association (ADA) DKA criteria were excluded. Patients with ketoacidosis secondary to other conditions  were also excluded. Additionally, recurrent DKA admissions from the same patient were excluded and not analysed. Patients were categorised into T1D and T2D and were further subdivided into new or pre-existing DM. We used International Classification of Diseases (ICD) codes to identify T1D and T2D in the EMR. We validated the accuracy of these codes in a subgroup of patients by looking at C-peptides and Anti-GAD antibodies where available. However, the levels were unavailable in most patients, so validation could not be done for all patients. Diagnosis of the type of DM relied mainly on the clinical judgment of the treating physicians.Data were extracted from the electronic health record, Cerner Millennium. Collected data included patients' demographic details, laboratory investigations on admission, and outcomes. We collected serum glucose, bicarbonate, lactate and PH levels in the following intervals: first value at admission, within the next 2 h (± 30 min), 4 h (± 30 min), and 6 h (± 30 min).2, overweight 23–24.9 kg/m2, obese ≥ 25 kg/m2. In all other ethnicities, BMI was defined as follows; normal < 25 kg/m2, overweight 25–26.9 kg/m2, obese ≥ 27 kg/m2. Patients were labelled as having high metabolic risk if one or more factors, including obesity, hypertension, and dyslipidemia, were identified.BMI was categorised into normal, overweight, and obese according to ethnicity. In Asians BMI was categorised as follows; normal < 23 kg/mDM was categorised as Newly diagnosed versus pre-existing T1D and T2D. NT1D group was defined as patients with DKA who were not known to have DM prior to admission and were subsequently diagnosed as having DM with positive anti-glutamic acid decarboxylase (GAD) antibodies (Ab) and/or low c-peptide levels. NT2D group was defined as patients with DKA who were not known to have DM prior to admission and were subsequently diagnosed as having DM with negative anti-GAD Ab and/or detectable c-peptide levels. Similarly, the PT1D group was defined as patients with T1D diagnosed before index admission with positive anti-glutamic acid decarboxylase (GAD) antibodies (Ab) and/or low c-peptide levels. Lastly, the PT2D group was defined as patients with T2D diagnosed before index admission with negative anti-glutamic acid decarboxylase (GAD) antibodies (Ab) and/or detectable c-peptide levels.The outcomes studied among the cohort of patients with index DKA admissions included the point prevalence of the type of DM, DKA severity, and serial biochemical evolution of DKA  in both DM types. DKA was diagnosed and categorised into mild, moderate or severe per the ADA DKA diagnostic criteria  . Random p-value ≤ 0.05 as significant.We used Stata version 15 for the statistical analysis. We summarised continuous variables as means (standard deviation (SD)) or medians (interquartile range (IQR)) as appropriate and categorical variables as percentages. Continuous variables were compared using the one-way ANOVA , while Chi-square and Fisher's exact test was used to compare categorical variables. We considered a P value < 0.001). The mean ages were 27.3 ± 0.5 years in pre-existing T1D (PT1D), 26.5 ± 9.6 years in new T1D (NT1D), 47.6 ± 13.1 years in pre-existing T2D (PT2D) and 42.6 ± 10.7 years in new T2D (NT2D) . PT1D were predominantly females (55%), while the other three groups were predominantly males . Comorbidities, including hypertension, dyslipidemia, and DM micro and macrovascular complications, were mainly found in patients with PT2D. Among the patients with NT2D, hypertension was present in 51 (28.9%), dyslipidemia in 22 (12.5%), microvascular complications of DM in 10 (5.6%), and macrovascular complications in 9 (5.1%) patients . High metabolic risk was seen in 62.4% of patients with PT2D and 61.9% with NT2D. In comparison, a high metabolic risk was present in 25.6% of patients with PT1D and 22.9% of patients with NT1D . Diabetes educator visits ranged from 56.8% in NT2D to 18% in PT1D . Detailed patients' demographics are presented in Table Of the 922 patients admitted with index DKA episodes during the study period, 480 patients (52%) had T1D, and 442 (48%) had T2D. The median duration of DM (at the time of admission) in patients with T1D and T2D was 7 (IQR 4–12) years and 5 (IQR 3–12) years, respectively . Anti GAD abs result at the time of index DKA admission were documented for 138 patients in total. Of the 51 patients with NT1D who had Anti GAD Abs documented, 30 (58.8%) had positive titres. Similarly, among 41 patients with NT2D with documented Anti GAD Abs, 3 (7.3%) had positive titres. Twenty-nine patients with PT2D had Anti GAD Abs checked, 6 (20.7%) having positive titres. Lastly, 17 patients with PT1D had Anti GAD abs checked, with 9 (52.9%) being positive. The creatinine clearance ranged from 96.6 ± 96.8 ml/min in patients with PT2D to 103 ± 51.5 ml/min in NT1D . The C-reactive protein (CRP) varied from 86.8 ± 136.5 mg/L in patients with NT2D to 26.2 ± 56.5 mg/L in patients with NT1D . Various triggering factors were reported, with non-compliance and infection being the most common . Non-compliance was reported as a triggering factor in 33.5% of patients with T1D and 23% of patients with T2D. Infection was the precipitating factor of DKA in 23.5% of patients with T1D and 29% of patients with T2D. The other triggering factors included pancreatitis, medication supply issues, and surgery . The biochemical evolution of DKA was similar among patients with T1D and T2D, with the only significant differences seen in venous lactate levels at 2, 4, and 6 h, which were higher in patients with T2D compared with patients with T1D . Bicarbonate, pH, and blood glucose changes in the first 6 h of DKA admission were not different among the four groups. EDKA  [Table atients) . Out of (Table ). Severe DKA was prevalent in all groups except PT1D, which had most patients with moderate DKA (42.1%) . LOS in hospitals ranged from 2.5 ± 3.5 days in patients with PT1D to 6.8 ± 11.3 days in patients with NT2D . Similarly, the DKA duration ranged from 18.9 ± 4.2 h in patients with PT1D to 26.6 ± 21.1 h in patients with NT2D . The ICU admission rates were 32% in patients with PT2D, and 31% in those with NT2D, whereas the ICU admissions in patients with NT1D and PT1D were 22.3% and 16.6%, respectively . Seven patients had in-hospital mortality  .DKA severity, LOS in the hospital, DKA duration, need for intensive care unit (ICU), and in-hospital mortality is tabulated Table . Severe We have presented one of the largest regional data on a diverse patient population showing the comparison between the different clinical and biochemical characteristics in patients of newly diagnosed and pre-existent T1D and T2D with index DKA admissions. Our study cohort had an equal proportion of patients with T1D and T2D. Patients with new and pre-existent T1D and T2D had different demographics and clinical characteristics, which translated into different DKA outcomes. Patients with PT1D were predominantly females, whereas all other groups had a male preponderance. The ethnic-specific BMI showed that patients with PT1D and NT1D were mainly within the normal range. On the other hand, patients with PT2D and NT2D had a significant proportion of the overweight and obese population. Comorbid conditions such as hypertension, dyslipidemia, and microvascular and macrovascular DM complications were predominantly seen in patients with PT2D, followed by NT2D, PT1D, and, lastly, NT1D. The metabolic risk was highest in PT2D patients, whereas the lowest metabolic risk was identified in patients with NT1D. Although patients with PT2D had the worst health status , LOS in the hospital and DKA duration were the longest in patients with NT2D . ICU admissions were needed in 31.2% and 32.3% of patients with NT2D and PT2D, respectively. However, patients with T1D had better outcomes, with the shortest LOS in hospital and DKA duration in PT1D  and the least frequency of ICU admissions. The evolution of DKA regarding serial laboratory investigations was similar in both DM types, except for serial lactate levels, which were higher in patients with T2D compared with those with T1D at 2, 4, and 6 h after admission. While a similar biochemical evolution reflects the same treatment of DKA in both DM types, outcomes do carry significant differences, mainly owing to different patient characteristics and DM type and duration.n = 176) on new versus pre-existing T1D and T2D in patients with DKA in 2004. In their study, PT1D comprised the majority  of DKA admissions, whereas NT1D and NT2D comprised 2.8% (5 patients) and 17% (30 patients) of total DKA admissions, respectively [We found an equal proportion of T1D and T2D among patients with DKA. This is different from other cohorts in which most patients had T1D. Ooi et al. reported 786 consecutive DKA episodes in a cohort with 75% of patients with T1D and 25% of patients with T2D . Similarectively . More reectively . Similarectively . The mosectively , showingMany factors have played a role in the increasing occurrence of DKA in patients with T2D, such as prolonged exposure to hyperglycemia. Many patients with newly diagnosed T2D, in fact, have relatively long-standing undiagnosed DM, which is translated as the presence of micro and macrovascular complications in such patients. This is primarily due to poor access to healthcare and relatively lower screening rates in some parts of the world . This prInterestingly, patients with NT2D in this study had worse DKA-related outcomes compared to other groups. These patients had the longest LOS in the hospital and the longest duration while in DKA, more than those with PT2D. LOS and DKA duration was much less in T1D subsets. Data from several studies have identified an association between T2D with a higher LOS in hospitals, with some studies reporting a four times more prolonged LOS in patients with T2D compared with T1D . A higheEpidemiological data identifying demographic and clinical differences in patients with new and pre-existing DM in various DM complication cases, such as DKA, are needed from different ethnic populations. Additionally, the high prevalence of T2D affecting the younger population, in addition to poor screening methods in large parts of the world, is resulting in a poor global T2D-related health burden. This calls for urgent steps to ensure regular screening to detect DM at earlier stages which can be controlled and possibly reverted before acute complications such as DKA can happen. A comprehensive national DM screening program is already in place in Qatar with similar aims . More efThe principal strength of our study lies in its extensive and diverse patient population, making the results generalisable to a vast geographic area. We identified and collected data from the index DKA admissions to find the most reliable proportion of DM types. The application of ADA DKA diagnostic criteria resulted in the exclusion of patients from the cohort but ensured an accurate representation of the cohort. Our study is, however, limited by its retrospective nature, due to which some covariates inherently could not be collected and might have influenced the results, such as anti-GAD Abs and C-peptide levels. This also limited our ability to validate the type of DM for each patient.T2D is increasingly causing DKA and causing a paradigm shift from a very low prevalence among the DKA population to an almost equal prevalence to T1D. DKA in T2D, especially NT2D, tends to have adverse outcomes. This can result in an increasing burden on healthcare and poor patient related DKA outcomes. As diabetes is influenced by environmental, geographical, and genetic variations, data presented in this study will help understand the differential evolution of DKA in similar patient populations. More studies from other ethnic groups are needed for a broader and global understanding of the epidemiological, clinical, and biochemical differences in DKA admissions based on the type and duration of DM.