Particularly challenging in this respect is UBE2D3, an E2 enzyme with promiscuous activity in vitro but less defined roles in vivo. Here, we set out to identify in vivo targets of UBE2D3 by using stable isotope labeling by amino acids in cell culture–based and label-free quantitative ubiquitin diGly proteomics to study global proteome and ubiquitinome changes associated with UBE2D3 depletion. UBE2D3 depletion changed the global proteome, with the levels of proteins from metabolic pathways, in particular retinol metabolism, being the most affected. However, the impact of UBE2D3 depletion on the ubiquitinome was much more prominent. Interestingly, molecular pathways related to mRNA translation were the most affected. Indeed, we find that ubiquitination of the ribosomal proteins RPS10 and RPS20, critical for ribosome-associated protein quality control, is dependent on UBE2D3. We show by Targets of Ubiquitin Ligases Identified by Proteomics 2 methodology that RPS10 and RPS20 are direct targets of UBE2D3 and demonstrate that the catalytic activity of UBE2D3 is required to ubiquitinate RPS10 in vivo. In addition, our data suggest that UBE2D3 acts at multiple levels in autophagic protein quality control. Collectively, our findings show that depletion of an E2 enzyme in combination with quantitative diGly-based ubiquitinome profiling is a powerful tool to identify new in vivo E2 substrates, as we have done here for UBE2D3. Our work provides an important resource for further studies on the in vivo functions of UBE2D3.Ubiquitination has crucial roles in many cellular processes, and dysregulation of ubiquitin machinery enzymes can result in various forms of pathogenesis. Cells only have a limited set of ubiquitin-conjugating (E2) enzymes to support the ubiquitination of many cellular targets. As individual E2 enzymes have many different substrates and interactions between E2 enzymes and their substrates can be transient, it is challenging to define all   •in vivo substrates of UBE2D3.SILAC-based and label-free diGly proteomics to identify •UBE2D3 affects CRABP1 and TSPAN8 protein levels.•UBE2D3 regulates ubiquitination of proteins involved in protein quality control.•in vivo.UBE2D3 ubiquitinates RPS10 and RPS20  in vivo substrates of the E2 ubiquitin-conjugating enzyme UBE2D3, we combined SILAC-based and label-free diGly-proteomics with UBE2D3 depletion. We show that UBE2D3 impacts CRABP1 and TSPAN8 levels and ubiquitinates key proteins in protein quality control. TULIP2 methodology identifies RPS10, RPS20, and SQSTM1 among direct targets of UBE2D3, and we show that UBE2D3's catalytic activity is required for RPS10 ubiquitination in vivo. Our approach identifies many potential UBE2D3 substrates, thereby providing a resource for future studies on UBE2D3 functions.To identify  Ubiquitination is a post-translational modification in which the conserved 76 amino-acid protein ubiquitin is attached to a lysine residue of a target protein by the combined actions of ubiquitin-activating E1) enzymes, ubiquitin-conjugating E2) enzymes, and ubiquitin E3) ligases. This mostly occurs through the formation of an isopeptide bond between the C-terminal glycine carboxyl moiety of ubiquitin and the ε-amino group of a lysine residue on the substrate protein, but ubiquitin can also be attached to the amino terminus of substrates. Deubiquitinating enzymes (DUBs) remove ubiquitin from targets, to maintain cellular ubiquitin homeostasis , a member of the UBE2D (or UBCH5) family of E2 enzymes . Furthermore, UBE2D3 levels affect responses to cancer cell treatment with radiation or all-trans retinoic acid (ATRA)  , 12. To in vivo substrates for UBE2D3 and used a modified TULIP2 (Targets of Ubiquitin Ligases Identified by Proteomics 2) methodology to confirm substrates as direct targets of UBE2D3  were described before and maintained at 32 °C . Cells were transduced with pRetrosuper-puro or pRetrosuper-blast retroviruses encoding shRNA targeting mouse and human UBE2D3 (Ube2d3 sh1): 5′-TGGGTTTGGATCACATATC-3′, for which we confirmed by quantitative RT–PCR (qRT–PCR) that it specifically depletes Ube2d3 and no other member of the UBE2D family. Control cells were transduced with empty pRetrosuper-puro or pRetrosuper-blast retrovirus. For the production of lentivirus, HEK 293T cells were transfected by CaPO4 precipitation with 10 μg of pLKO-puro shRNA lentiviral vectors obtained from Mission library clones (Sigma). Medium was refreshed at 16 h after adding the DNA–CaPO4 precipitate, and viral supernatants were collected at approximately 48 h post-transfection. Viral supernatants were either frozen in liquid nitrogen and stored at −80 °C until use or used immediately. For lentiviral infection, target cells were incubated for 16 h with viral supernatant that was supplemented with 4 μg ml−1 polybrene. Viral transduction was confirmed by acquired resistance to 2 μg ml−1 puromycin (Invitrogen). The following lentiviral shRNAs were used: human UBE2D3 shRNA #1 TRCN0000038792: 5′-CCAGAGATTGCACGGATCTAT-3′, human UBE2D3 shRNA #2 TRCN0000038790: 5′-GCCTGCTTTAACAATTTCTAA-3′, mouse Ube2d3 shRNA #2 TRCN0000039469: 5′-ACAACAGAATATCTCGGGAAT-3′, and scrambled nontargeting shRNA: 5′-CAACAAGATGAAGAGCACCAA-3′. Human UBE2D3 WT and C85A mutant complementary DNA (cDNA) were cloned into a pCDH-puro backbone using traditional cloning and were used for lentiviral infections.For the production of retrovirus, ecotropic phoenix producer cells were seeded on a 10 cm dish and transfected with 20 μg of retroviral vector DNA using CaPOUbe2d3 shRNA-transduced MEFs were grown in either light or heavy SILAC medium  arginine(10) Kit; catalog no.: 282986434, Silantes), supplemented with 10% fetal bovine serum, 2 ml glutamine, 100 U penicillin, and 0.1 mg ml−1 streptomycin. Control MEFs were grown in light medium . Ube2d3 shRNA1-transduced MEFs were grown in heavy medium . Cells were cultured for at least two weeks in SILAC light or heavy medium before the experiments were done to accomplish complete labeling. The SILAC experiments were performed and analyzed as six replicates.Control (pRetrosuper) or Cells grown in SILAC light or heavy medium were harvested for global proteome and ubiquitinome analyses. Cells were washed three times with ice-cold PBS and lysed in 200 μl of an 8 M urea/50 mM Tris–HCl (pH 8.0)/50 mM NaCl lysis buffer. Lysates were incubated on ice for 10 min and sonicated, debris was removed by centrifugation, and protein concentrations were determined using a bicinchoninic acid (BCA) assay (Pierce). Control and UBE2D3-depleted samples were mixed in a 1:1 ratio based on total protein content. An amount of 20 mg protein was used for diGly peptide enrichment for ubiquitinome analyses; for global proteome analyses, 0.5 mg lysate was used.2 . Proteins were digested with sequencing grade trypsin  overnight at room temperature. Alternatively, proteins were digested with LysC  for 1 h at room temperature before trypsinization. Protein digests were then desalted using a Sep-Pak tC18 Vac cartridge (Waters) and eluted with 80% acetonitrile (AcN). Tryptic peptides were fractionated by hydrophilic interaction liquid chromatography on an Agilent 1100 HPLC system using a 5 μm particle size 4.6 × 250 mm TSKgel amide-80 column (Tosoh Biosciences). An amount of 200 μg of tryptic digest in 80% AcN was loaded onto the column. Peptides were eluted using a nonlinear gradient from 80% B (100% AcN) to 100% A (20 mM ammonium formate in water) with a flow of 1 ml/min. A total of 16 6 ml fractions were collected, lyophilized, and pooled into eight final fractions. Each fraction was then analyzed by nanoflow LC–MS/MS.Protein lysates were reduced with 10 mM DTT for 1 h at room temperature followed by alkylation with 55 mM chloroacetamide for 1 h in the dark. The mixture was diluted four times with 50 mM ammonium bicarbonate buffer before the addition of CaClDiGly-modified peptides were enriched by immunoprecipitation using PTMScan ubiquitin remnant motif (K-Ɛ-GG) antibody bead conjugate  starting from 20 mg total protein, essentially according to the manufacturer’s protocol. Unbound peptides were removed by washing, and the captured peptides were eluted with a low pH buffer. Eluted peptides were analyzed by nanoflow LC–MS/MS.m/z range 350 to 1700. Fragmentation of precursors was performed in data-dependent mode by high energy collisional dissociation (Top15) with a precursor window of 3.0 m/z and a normalized collision energy between 26.0 and 28.0; MS2 spectra were recorded in the ion trap. Singly charged precursors were excluded from fragmentation. Dynamic exclusion was set to 20 s, and the intensity threshold was set to 8.0E3. For the ubiquitinome analysis, a single LC–MS/MS run was performed for all immunoprecipitated peptide material from one sample.Nanoflow LC–MS/MS was performed on an EASY-nLC system (Thermo) coupled to a Fusion Lumos Tribrid Orbitrap mass spectrometer (Thermo), operating in positive mode, and equipped with a nanospray source. Peptide mixtures were trapped on a ReproSil C18 reversed-phase column  at a flow rate of 8 μl/min. Peptide separation was performed on ReproSil C18 reversed-phase column  using a linear gradient from 0 to 80% B  in 70 or 120 min and at a constant flow rate of 250 nl/min. The column eluent was directly sprayed into the electrospray ionization source of the mass spectrometer. All mass spectra were acquired in profile mode. The resolution in mass spectrometry 1 (MS1) mode was set to 70,000 (automatic gain control [AGC]: 3E6), the https://www.maxquant.org/)  concatenated with the reversed versions of all sequences and a contaminant database listing typical background proteins. A maximum of two missed cleavages were allowed. MS/MS spectra were analyzed using MaxQuant’s default settings for Orbitrap and ion trap spectra. The maximum precursor ion charge state used for searching was 7, and the enzyme specificity was set to trypsin. Further modifications were cysteine carbamidomethylation (fixed) as well as methionine oxidation and lysine ubiquitination (variable). The minimum number of peptides for positive protein identification was set to 2. Heavy-to-light (H:L) ratios were calculated using MaxQuant’s default settings, including a minimum ratio count of 2 for label-based protein quantification and of 1 for diGly peptide quantification. The minimum number of razor and unique peptides was set to 1. Only unique and razor nonmodified, methionine oxidized, and protein N-terminal acetylated peptides were used for protein quantitation. The minimal score for modified peptides was set to 40 . The “requantify” option was selected in all cases. Only proteins that were identified and quantified in both duplicates and with consistent ratios were considered for further analysis. The proteingroups.txt, modificationspecificpeptides.txt, and GlyGly_(K)sites.txt output tables were all processed in R . Reverse hits (decoys) and potential contaminants were filtered excluded from analysis. Normalized ratios of all replicate experiments were Log2 transformed, and these values were used in a one sample two-sided t test (mu = 0) to calculate p values. The modificationspecificpeptides.txt table was further adjusted by adding the diGly sites probability column from the GlyGly_(K)sites.txt table. Protein sets were further analyzed with Perseus   (https://string-db.org/)   for idenerseus/) , throughnalysis) , STRING db.org/)  and in-hdb.org/) . For staUbe2d3 shRNA1, and Ube2d3 shRNA2). Cells were washed twice with ice-cold PBS. Lysis, digestion, and enrichment of ubiquitinated peptides was performed according to the PTMScan HS K-ϵ-GG Remnant Magnetic Immunoaffinity Beads Kit protocol . Briefly, cell pellets were lysed in 1× S-Trap lysis buffer, sonicated with a probe, and lysates were cleared by centrifugation. Equal protein amounts (2 mg per sample) were reduced with DTT, alkylated with chloroacetamide, and digested overnight at 37 °C with trypsin  using S-Trap Midi cartridges (ProtiFi). Peptides were eluted with elution buffers 1 to 3, after which 20 μg aliquots were taken for proteome analysis, the remainder being reserved for ubiquitinated peptide enrichment. All samples were dried in a Speedvac and stored at −80 °C until LC–MS/MS or further processing. Immunoaffinity purification of ubiquitinated peptides was performed with K-ϵ-GG Remnant Magnetic Immunoaffinity Beads using the manufacturer’s instructions. Ubiquitinated peptides were eluted twice with 50 μl 0.15% TFA and concentrated with C18 stage tips .Six 15 cm diameter plates of MEFs were grown and harvested for each condition  were acquired at 60,000 resolution with an AGC target of 3 × 106 charges and maximum injection time of 45 ms. Loop count was set to 20, and only precursors with charge state 2 to 7 were sampled for MS2 using 15,000 resolution , MS2 isolation window of 1.4 m/z, 1 × 105 AGC target, a maximum injection time of 22 ms (or 54 ms for ubiproteome), and a normalized collision energy of 26.Prior to MS analysis, peptides were reconstituted in 2% FA. Peptide mixtures were analyzed by nanoLC-MS/MS on an Q Exactive HF-X Hybrid Quadrupole-Orbitrap Mass Spectrometer equipped with an EASY-NLC 1200 system (Thermo Scientific). Samples were directly loaded onto the analytical column . Solvent A was 0.1% FA/water, and solvent B was 0.1% FA/80% AcN. Samples were eluted from the analytical column at a constant flow of 250 nl/min. For single-shot proteome analysis, a 210-min gradient containing a linear 194-min increase from 6 to 26% solvent B was used, whereas a 144-min gradient containing a linear 124-min increase from 4 to 24% solvent B was used for ubiproteome analysis. MS settings were as follows: full MS scans (375–1500 t test (cutoffs: p < 0.05 and LFQ differences log2 ≥ 1.0 and log2 ≤ −1.0). Annotated spectra have been deposited to MS-Viewer: For proteome, the link is: https://msviewer.ucsf.edu/prospector/cgi-bin/mssearch.cgi?report_title=MS-Viewer&search_key=3opswum57r&search_name=msviewer (key: 3opswum57r), and for the diGly dataset, the link is: https://msviewer.ucsf.edu/cgi-bin/mssearch.cgi?report_title=MS-Viewer&search_key=kapdokzmqp&search_name=msviewer (key: kapdokzmqp). Zipped MaxQuant data have been deposited to the PRIDE repository with the data identifier PXD035045.Proteome and ubiproteome data (RAW files) were analyzed by label-free quantitation (LFQ) using MaxQuant (version 1.6.17.0)  with staUBE2D3-TULIP2 samples were prepared as previously described , UBE2D3 Five 15 cm diameter plates of HeLa cells were grown up to 60 to 80% confluency. Expression of UBE2D3-TULIP2 constructs was induced with 1 μg/ml doxycycline for 24 h, and cells were untreated or treated for 5 h with 10 μM proteasome inhibitor MG132 (Sigma–Aldrich). Next, cells were washed twice with ice-cold PBS, scraped, and lysed in 10 ml guanidinium buffer . Samples were homogenized at room temperature by sonication using a tip sonicator . Protein concentration was determined by using BCA Protein Assay Reagent (Thermo Scientific) and equalized accordingly.Once equalized, lysates were supplemented with 5 mM β-mercaptoethanol and 50 mM imidazole (pH 7.8). For each sample 100 μl of nickel–nitrilotriacetic acid (Ni–NTA)–agarose beads (QIAGEN) were equilibrated with guanidinium buffer supplemented with 5 mM β-mercaptoethanol and 50 mM imidazole (pH 7.8), added to the cell lysates, and incubated overnight at 4 °C under rotation. Next, Ni–NTA beads were transferred with wash buffer 1  to an Eppendorf LoBind tube (Eppendorf) and sequentially washed with wash buffer 2 , wash buffer 3 , and twice with wash buffer 4 . In every wash step, beads were allowed to equilibrate with the buffer for 15 min under rotation.Ni–NTA beads were resuspended in one bead volume of elution buffer without imidazole  and incubated with 375 ng of rLys-C (Promega) for 5 h at 37 °C on a shaker at 1400 rpm. Subsequently, four volumes of 50 mM ammonium bicarbonate were added to the samples, and a second digestion using 500 ng trypsin (Promega) was done overnight at 37 °C and 1400 rpm for a complete digestion. Resulting peptides were purified and desalted using C-18 StageTips .m/z and resolutions of 60,000 and 30,000 for MS1 and MS2, respectively. For MS2, an isolation window of 1.6 m/z and a high energy collisional dissociation energy of 28% was applied. Precursors with a charge of 1 and higher than 6 were excluded from triggering MS2 as well as previously analyzed precursors with a dynamic exclusion window of 30 s.UBE2D3 samples were analyzed in an Orbitrap Exploris 480 (Thermo Fisher Scientific) mass spectrometer coupled to an Ultimate 3000 UHPLC (Dionex). Digested peptides were separated using a 50 cm long fused silica emitter  in-house packed with 1.9 μm C18-AQ beads  and heated to 50 °C in a column oven for electrospray ionization/Nano Spray (Sonation). Peptides were separated by liquid chromatography using a gradient from 2% to 32% AcN with 0.1% FA for 100 min followed by column reconditioning for 20 min. A lock mass of 445.12003 (polysiloxane) was used for internal calibration. Data were acquired in a data-dependent acquisition mode with a TopSpeed method with cycle time of 3 s with a scan range of 300 to 1600 et al. . Oxidation (M), acetyl (protein N-term), GlyGly (K), and Phospho (STY) were set as variable modifications with a maximum of 3. Carbamidomethyl (C) was disabled as fixed modification. LFQ was activated not enabling fast LFQ. FDRs at the peptide and protein level were 0.01. The match between runs feature was activated with default parameters.MS data were analyzed using MaxQuant, version 1.6.14.0 according to Tyanova et al.  with theet al.  (https://msviewer.ucsf.edu/cgi-bin/mssearch.cgi?report_title=MS-Viewer&search_key=lqf88o5m68&search_name=msviewer (key: lqf88o5m68).MaxQuant output data were further processed in the Perseus Computational Platform v1.6.14 according to Tyanova et al. . LFQ intterburg) . AnnotatHprt was used as a reference for transcript expression. Transcripts were amplified using the following primers for mouse Tspan8 forward: 5′-CTGACTGTGCAACTTATCA GG-3′ and mouse Tspan8 reverse: 5′-GCCAGTCCAAAAGCAATTCC-3′; for mouse Crabp1 forward: 5′-CGGAGATCAACTTCAAGGTCGG-3′ and mouse Crabp1 reverse: 5′-CCCTCAAGAAGTGTCT GTGTGC-3′; for mouse Hprt forward: 5′-CTGGTGAAAGGACCTCTCG-3′ and mouse Hprt reverse: 5′-TGAAGTACTCATTATAGTCAAGGGCA-3′. Data were analyzed according to the 2-ΔCt methodology.To determine gene expression levels, total RNA was isolated using TRIzol reagent (Ambion) and reverse transcribed into cDNA using the Tetro cDNA Synthesis kit  with Oligo(dT) primers. Quantitative real-time PCR was performed using the SensiFAST SYBR No-ROX kit  on a QuantStudio 5 Flex real-time PCR system (Thermo Fisher Scientific). For immunoprecipitation with ectopically expressed V5-tagged constructs, control (nontargeting shRNA) and UBE2D3-depleted HEK 293T cells were cotransfected with pcDNA3.1(+)-hemagglutinin (HA)-ubiquitin  and eithWhole-cell lysates were prepared by scraping cells in SDS sample buffer . Lysates were sheared with a 25G needle and boiled for 10 min at 95 °C. Protein concentration was determined by standard BCA protein assay (Pierce). Equal amounts of protein were separated on precast polyacrylamide gels (Invitrogen). Immunoblotting was done according to standard methods using IRDye800CW- and IRDye680-labeled secondary antibodies for detection on the Odyssey Infrared imager (LI-COR) or using horseradish peroxidase–conjugated secondary antibodies for detection by enhanced chemiluminescence . Primary antibodies used were against UBE2D , V5 , HA , FLAG , RPS20 , Histone H3 , CRABP1 , TSPAN8 , GAPDH , HSP90 α/β , β-actin , and γ-tubulin .Ube2d3 shRNA1) was studied with respect to its appropriate control (control shRNA). Six biological replicates of both sample and control were performed in a “forward” SILAC fashion, resulting in a total number of 12 samples. For every sample, the appropriate control was analyzed in the same experiment, that is, sample in the SILAC heavy channel and control in the SILAC light channel. Statistical analysis was performed using a two-sided one-sample t test, which is appropriate for SILAC H:L ratio analysis based on multiple replicates.The number of samples in the SILAC-based diGly proteomics was two, since one experimental condition (Ube2d3 shRNA1 and Ube2d3 shRNA2), three biological replicates were used for comparison of protein or ubiquitinated peptide LFQ abundances, as this number of replicates is the minimum number of replicates required in order to be able to reliably use a two-sided Student’s t test for comparison of each shRNA cell line versus the WT control condition.For all three experimental conditions in the LFQ diGly proteomics  or the medium with heavy lysine and arginine isotopes (Ube2d3 sh1 cells) to completely label all proteins with heavy amino acids. Subsequently, cells were harvested, lysed, and mixed at a 1:1 protein content ratio. The samples were digested and used for both global proteome analysis and ubiquitinome analysis after ubiquitin diGly-peptide enrichment (A). Experiments were performed as six biological replicates, all in a forward fashion and after confirming the reduction in UBE2D3 protein levels in heavy-labeled Ube2d3 sh1 cells compared with light-labeled control cells (A). To exclude potential off-target effects of the shRNA used against Ube2d3 (shRNA1) in the SILAC-based diGly proteomics analysis, we performed an independent validation including a second independent shRNA (shRNA2) targeting Ube2d3, in a label-free setting (LFQ). P53-deficient MEFs were transduced with control shRNA, Ube2d3 shRNA1, or Ube2d3 shRNA2 and used for global proteome analysis and for ubiquitinome analysis after diGly-peptide enrichment . Experiments were performed as three biological replicates.To identify richment A. Experiol cells A. To excC and supplemental Fig. S1C). For 35 of these proteins, the increase was statistically significant (p ≤ 0.05), and for 91 proteins, their decrease was statistically significant . For the LFQ proteomics, the results show that with both shRNAs around 3700 proteins were identified in at least two of three experiments . Combined, the results of the SILAC-based and label-free approaches indicate that UBE2D3 not only decreases the levels of certain proteins by for instance promoting their degradation but also (indirectly) increases the levels of certain other proteins. However, the low numbers of proteins affected indicate that UBE2D3 only has a modest role in regulating protein abundance.The experiments were performed without addition of proteasome inhibitors, causing some targets of UBE2D3 to be potentially missed because of proteasomal degradation, but allowing assessment of the dynamics of protein abundance upon UBE2D3 depletion. For the SILAC-based proteomics, typically over 6300 proteins were identified per experiment . As can be expected with depleting an E2 enzyme that would most likely result in loss of ubiquitination of its targets, the number of peptides that decreased in ubiquitination is substantially higher than the number of peptides that increased in ubiquitination. Over 13,000 peptides were diGly modified in at least two of six experiments, of which 77 peptides were significantly (p ≤ 0.05) increased in their ubiquitination and 1186 peptides were significantly decreased in their ubiquitination in UBE2D3-depleted cells  in their ubiquitination and 665 were significantly decreased in their ubiquitination in UBE2D3-depleted cells . Thus, we found UBE2D3 to significantly affect the ubiquitination status of ±9.5% of all detected diGly-modified peptides, corresponding to ±15% of the total amount of diGly-modified proteins. Of these, 0.6% of the diGly-modified peptides and 1.4% of the diGly-modified proteins were increased in their ubiquitination, and 8.8% of the diGly-modified peptides and 13.5% of the diGly-modified proteins were decreased in their ubiquitination upon depletion of UBE2D3 (E and F). Label-free ubiquitinome analysis revealed 5831 diGly-modified peptides over all experiments . A total of 101 peptides, representing 90 unique proteins, were significantly increased in their ubiquitination upon UBE2D3 depletion, whereas 183 peptides, representing 164 unique proteins, were decreased in their ubiquitination  (E and F and E and F). Thus, in contrast to the promiscuous behavior of UBE2D3 seen under in vitro conditions, in vivo UBE2D3 is a quite selective E2 enzyme, only affecting a small portion of the total number of identified diGly-modified proteins and peptides.SILAC-based ubiquitinome analysis revealed over 19,000 diGly peptides over all experiments. In total, almost 500 peptides were ≥1.5-fold increased in ubiquitination, whereas over 3500 peptides were ≥1.5-fold decreased in ubiquitination upon UBE2D3 depletion D. As canA and p ≤ 0.05) change in abundance for further analysis , and the LFQ with Ube2d3 sh2 (LFQ sh2), we found only CRABP1 to be significantly increased in abundance in all three experiments, and only TSPAN8 to be significantly decreased in abundance in all three experiments (D–F). When assessing the overlap between 2 out of 3 SILAC or LFQ experiments, we found three additional proteins that increased in abundance and five additional proteins that decreased in abundance , the LFQ with eriments , D–F. Wh D–F and . In geneA, B, C, and F), UBE2D3 might promote degradation of CRABP1 and thereby impact RA signaling. To address this hypothesis, we assessed CRABP1 protein levels in immunoblots of protein lysates from control cells and UBE2D3-depleted cells, treated with and without the proteasome inhibitor MG132 . Indeed, we found CRABP1 protein levels to be increased upon UBE2D3 depletion, thereby validating the proteomics results. However, MG132 treatment of up to 16 h, which was the maximum duration tolerated by the cells, did not lead to clearly visible CRABP1 protein stabilization, which precluded us from confirming that UBE2D3 promotes proteasomal degradation of CRABP1 . Nevertheless, qRT–PCR analysis indicated that the increased CRABP1 protein levels upon UBE2D3 depletion are not accompanied by increased Crabp1 mRNA levels, indicating that UBE2D3 regulates CRABP1 on protein level .CRABP1 is a protein that responds to retinol (vitamin A) signaling by binding to RA (a metabolite of retinol). In the nucleus, RA binds and activates RA receptors, eventually resulting in transcription of target genes and thereby regulating differentiation and proliferation . CRABP1 A, B, C, and F). To independently validate the impact of UBE2D3 on TSPAN8 protein levels and to investigate if this is dependent on the proteasome, we assessed TSPAN8 protein levels in immunoblots of protein lysates from control cells and UBE2D3-depleted cells, treated with and without the proteasome inhibitor MG132 . Indeed, UBE2D3-depleted cells express lower levels of TSPAN8 protein, confirming the proteomics results. However, MG132 barely affected TSPAN8 protein levels over the duration of treatment, prohibiting us from determining the involvement of proteasomal degradation in the regulation of TSPAN8 levels by UBE2D3 . However, qRT–PCR analysis indicated that the decreased TSPAN8 protein levels upon UBE2D3 depletion are not because of decreased Tspan8 mRNA levels. Upon the expression of Ube2d3 shRNA1 TSPAN8, transcript levels were even significantly increased over three independent biological replicates. Thus, the reduced TSPAN8 protein levels in UBE2D3-depleted cells seem to result from regulation at the protein level .TSPAN8 is a cell surface glycoprotein belonging to the transmembrane protein family of tetraspanins that function in intracellular signal transduction, cell adhesion, and motility. It forms a complex with integrins, which promote cell–cell and cell–matrix adhesion , 42, 43.in vivo, we subsequently focused on the ubiquitinome changes occurring upon UBE2D3 depletion in our SILAC-based diGly proteomics and LFQ diGly proteomics data, represented by diGly peptides with a normalized ratio of ≥1.5-fold (SILAC) or ≥2-fold (LFQ) that were significantly changed (p ≤ 0.05) (A and B and To identify novel direct and indirect targets of UBE2D3 Ube2d3 sh1) and 90 (LFQ Ube2d3 sh2) proteins that were significantly increased ≥1.5-fold (SILAC) or ≥2-fold (LFQ) in their ubiquitination upon UBE2D3 depletion and most likely represent indirect targets of UBE2D3 , and PEG10) increased in abundance in LFQ Ube2d3 sh2   in ubiquitination of targets, such as DCNL1, β-catenin, Myc, and IκBα . Of these seven proteins, three proteins were found to be modified on the same lysine in the SILAC and LFQ diGly experiments, further supporting that these proteins are potential new indirect targets of UBE2D3. Among these, SLC14A1 was also increased in abundance upon UBE2D3 depletion in the SILAC sh1 condition ; therefore, the observed increase in ubiquitination could potentially be a consequence of increased abundance. However, for MPRIP and 14-3-3θ (YWHAQ), no change in abundance was observed, further supporting that these proteins are new indirect ubiquitination targets of UBE2D3. MPRIP is a filamentous actin-binding protein that can affect the integrity of the actin cytoskeleton , which is known to interact with UBE2D3 and to be ubiquitinated at K420 by UBE2D3 to activate its function as an autophagy receptor . Human aFig. 3radation . By reguUbe2d3 sh1 and LFQ Ube2d3 sh2 diGly proteomics (B). TAX1BP1 and BIRC2 are both involved in regulation of NF-κB signaling  following UBE2D3 depletion. These proteins have different biological functions, for example, in protein degradation, post-translational protein modification, and cytoskeleton support . We also evaluated if the decreased ubiquitination of these 50 proteins upon UBE2D3 depletion could be a consequence of decreased abundance. However, we found no indication for this as there was no overlap between these 50 proteins and the proteins decreasing in abundance in the corresponding global proteome data from SILAC sh1 and LFQ sh2 (B and C). The top hits that were affected by UBE2D3 depletion with both sh1 and sh2, and are related to mRNA translation, are the 40S ribosomal proteins RPS10 and RPS20. Both were >2.5-fold reduced in their ubiquitination upon UBE2D3 knockdown . After generation of HeLa cells with stably integrated TULIP2 constructs with UBE2D3 WT, UBE2D3 C85A , and UBE2D3 WT with a ubiquitin lacking the diGly motif (ΔGG) as a negative control, expression was induced with doxycycline and the cells were untreated or treated with proteasome inhibitor (MG132) to prevent degradation of ubiquitinated substrates of UBE2D3. Subsequently, substrates covalently attached to TULIP2-UBE2D3 constructs, through interaction of UBE2D3 with different E3 ligases, were purified using Ni–NTA beads, and peptides were analyzed by MS .The diGly proteomics approaches that we used here successfully identified a considerable number of potential novel targets for UBE2D3 but are not able to distinguish between direct and indirect substrates of UBE2D3. Therefore, we used the TULIP2 methodology , originaFig. 5C and D and supplemental Fig. S5B). These include not only the top hits RPS10 and RPS20, but also SQSTM1, which is a known target of UBE2D3  . TULIP2 f UBE2D3 . In addif UBE2D3 , demonstUbe2d3 sh1 diGly proteomics but no change in RPS3-K214 ubiquitination in the LFQ Ube2d3 sh2 diGly proteomics. We found RPS3A-K249 ubiquitination reduced in the LFQ sh2 experiments, but this was not statistically significant and therefore not considered as a hit, whereas RPS3A peptides with Ub modification on K249 were not identified in SILAC sh1 experiments . Of these, peptides ubiquitinated on both K138 and K139 were more frequently observed than peptides with only one of these sites modified. From the diGly-peptides recovered for RPS20, all peptides ubiquitinated on K4 and/or K8 were decreased in UBE2D3 knockdown cells, with both shRNAs (A and B). Also here, mainly peptides modified on both K4 and K8 were found. Importantly, the abundance of RPS10 or RPS20 was not affected by UBE2D3 depletion, thus the observed decrease in their ubiquitination is not caused by lower protein abundance . In addition, we also confirmed decreased RPS20 ubiquitination upon UBE2D3 depletion in HEK 293T cells (D and E). Moreover, we show that ubiquitination of RPS10 by UBE2D3 in vivo is dependent on the catalytic activity of UBE2D3, as overexpression of UBE2D3 WT, but not UBE2D3 C85A, resulted in increased ubiquitination of RPS10 (E and F). Hence, despite redundancy between UBE2D family members and E2 enzymes in general, UBE2D3 seems to be the main E2 that ubiquitinates RPS10 in the MEFs used in our proteomics experiments as well as in the human HeLa cells used in TULIP2 experiments, and in HEK 293T cells used for in vivo ubiquitination experiments. Thus, here we demonstrate that UBE2D3 ubiquitinates RPS10 and RPS20 in vivo, supporting a role for UBE2D3 in the degradation of aberrant nascent polypeptides through the RQC pathway.Ubiquitination of RPS10 on K138/139 is critical for proper RQC , 23. To 3T cells , D and Eof RPS10 , E and FSaf1 and HRD1, and of DUBs such as USP32 and CYLD . Interestingly, ALDH1A1, identified as a hit with decreased abundance in both LFQ experiments with two independent Ube2d3 shRNAs, is also involved in retinol signaling . In the SILAC-based proteomics, ALDH1A1 also decreased in abundance but was not selected as a hit from that data because its change did not meet the threshold for significance . ALDH1A1 is a retinol dehydrogenase that converts retinaldehyde to RA and thereby plays an important role in retinol metabolism  in various cancers, including pancreatic, lung, breast, ovarian, colon, liver, and gastric cancers . High TSin vivo, and through direct immunoprecipitation of RPS10 and RPS20 from cells, we confirmed that their ubiquitination is indeed dependent on UBE2D3. In addition, through TULIP2 methodology, we identified RPS10 and RPS20 as direct substrates of UBE2D3. Moreover, immunoprecipitation experiments in HEK 293T cells confirmed that the catalytic activity of UBE2D3 as an E2 enzyme is required for ubiquitination of RPS10 in vivo, further supporting that RPS10 is a direct target of UBE2D3. In the absence of ZNF598-mediated ubiquitination of RPS10-K138/139 and RPS20-K4/8, execution of RQC is compromised  in UBE2D3-depleted cells  and S10.Fig. 6via SQSTM1, HSPA5, and TAX1BP1. This indicates that next to preventing the production of defective proteins via RQC, UBE2D3 can also contribute to the removal of dysfunctional proteins and their aggregates via PQC. SQSTM1 and HSPA5 dysregulation has been implicated in neurodegenerative disorders, such as Alzheimer’s disease and Parkinson’s disease , and for the diGly dataset, the link is: https://msviewer.ucsf.edu/cgi-bin/mssearch.cgi?report_title=MS-Viewer&search_key=kapdokzmqp&search_name=msviewer (key: kapdokzmqp).For proteome, the link is: https://msviewer.ucsf.edu/cgi-bin/mssearch.cgi?report_title=MS-Viewer&search_key=lqf88o5m68&search_name=msviewer (key: lqf88o5m68).For TULIP2, MS annotated spectra have been deposited to MS-Viewer: This article contains The authors declare no competing interests.


Herein, ZnmIn2S3+m (m = 1–5) semiconductors  with various composition faults were synthesized via a simple hydrothermal method and used for effective selective dehydrocoupling of benzyl alcohol into high-value C–C coupling products and reduction of CO2 into syngas under visible light. The absorption edge of ZnmIn2S3+m samples shifted to shorter wavelengths as the atomic ratio of Zn/In was increased. The conduction band and valence band position can be adjusted by changing the Zn/In ratio, resulting in controllable photoredox ability for selective BA oxidation and CO2 reduction. For example, the selectivity of benzaldehyde (BAD) product was reduced from 76%  to 27% , while the selectivity of hydrobenzoin (HB) was increased from 22% to 56%. Additionally, the H2 formation rate on ZIS1 (1.6 mmol/g/h) was 1.6 times higher than that of ZIS4 (1.0 mmol/g/h), and the CO formation rate on ZIS4 (0.32 mmol/g/h) was three times higher than that of ZIS1 (0.13 mmol/g/h), demonstrating that syngas with different H2/CO ratios can be obtained by controlling the Zn/In ratio in ZnmIn2S3+m. This study provides new insights into unveiling the relationship of structure–property of ZnmIn2S3+m layered crystals, which are valuable for implementation in a wide range of environment and energy applications.Integrating photocatalytic CO The Mott–Schottky curves indicated the samples exhibited n-type characteristics due to the positive slopes, and their flat-band potential was estimated to be −0.57, −0.59, −0.61, −0.65, −0.70 V vs. reversible hydrogen electrode (RHE), respectively  under the irradiation of visible light (λ > 420 nm) was studied using ZnmIn2S3+m samples  ≈ ZIS4 (0.32 mmol/g/h) > ZIS3 (0.17 mmol/g/h) > ZIS2 (0.15 mmol/g/h) > ZIS1 (0.13 mmol/g/h). This suggests that with increasing Zn content, the electrons preferentially react with CO2 rather than H+. The BET-specific surface area of the ZIS1 and ZIS4 samples was also measured using CO2 adsorption–desorption analysis . The corresponding data can be found in −1 were attributed to the presence of bidentate carbonate (b-CO32−) . A. A2RR ane in BAD . The strH) modes , which cmIn2S3+m samples were synthesized by a simple hydrothermal method. For each preparation, 0.8 mmol ZnSO4·4H2O, 1.6 mmol InCl3·4H2O, 0.65 g CTAB, and 7 mmol thioacetamide (TAA) were dispersed into 70 mL deionized water. After stirring for 60 min, the above suspension was transferred into a 100 mL Teflon-lined autoclave  and heated at 160 °C for 12 h. After natural cooling to room temperature, the precipitate was washed with absolute ethanol and deionized water several times and dried at 60 °C in a vacuum oven. The as-obtained samples, ZnIn2S4, Zn2In2S5, Zn3In2S6, Zn4In2S7, and Zn5In2S8 were defined as ZIS1, ZIS2, ZIS3, ZIS4, and ZIS5, respectively.Zn−1. Fourier transform infrared spectroscopy (FT-IR) was measured on an iS50 . The optical properties were characterized by UV-Vis diffuse reflectance spectroscopy (UV-Vis DRS) using a UV-Vis spectrophotometer . N2 physisorption measurements were carried out at 77 K using a Micromeritics Tristar II 3020 surface area analyzer. Multipoint Brunauer-Emmett-Teller (BET) specific surface areas were then determined from the adsorption isotherms . The X-ray photoelectron spectroscopy (XPS) was measured on a Thermo Fischer ESCALAB Xi+ spectrometer with an Al Kα X-ray beam . The binding energies were corrected regarding the C 1s peak of the surface adventitious carbon at 284.8 eV. Transmission electron microscopy (TEM) and high-resolution transmission electron microscopy (HRTEM) images were performed on a JEM-2100 with an accelerating voltage of 200 kV . The morphologies of the photocatalysts were carried out by scanning electron microscope .The structures of samples were analyzed by powder X-ray diffraction (XRD) using a Bruker D8 advance X-ray diffractometer  with Cu Kα radiation (λ = 0.1540 nm) and a scanning speed of 3· min−1 Na2SO4 solution. Electrochemical impedance spectra (EIS) are carried out in a mixture of 0.1 mol L−1 KCl and 0.1 mol L−1 K3[Fe(CN)6]/K4[Fe(CN)6].Photoelectrochemical measurements: A 5 mg sample was dispersed in 400 μL of deionized water by sonication to obtain a uniform slurry. Then, 20 μL of slurry was deposited as a film on a 0.5 cm × 0.5 cm fluorine-doped tin oxide (FTO) conducting glass to obtain the working electrode. After drying at room temperature, the working electrode was obtained. Ag/AgCl was used as a reference electrode, and platinum wire as a counter electrode. The photocurrent test and flat band potential (M-S plots) were carried out in a three-electrode system in a 0.2 mol L2 reduction and benzyl alcohol oxidation was tested in a visible high-temperature and high-pressure reactor. Typically, 5 mg photocatalyst and 5 mL acetonitrile containing 5 mM benzyl alcohol and 0.1 g K2CO3 were added into the reactor, which was then ultrasonicated to ensure even dispersion of the catalyst. The reactor was then vacuumed to remove air and finally was stirred in the dark for 30 min to achieve a dynamic dissolution equilibrium of CO2 in an atmosphere of CO2 gas. The Xe lamp (λ > 420 nm) was used to provide the light source for the reaction. Gas products were collected using a gas injection needle with a quantitative ring, and CO and other products were detected by a flame ionization detector (FID), while H2 was detected by a thermal conductivity detector (TCD) gas chromatograph. The liquid products were collected, diluted with acetonitrile, and detected by high-performance liquid chromatography (HPLC).The coupling activity of photocatalytic CO2 and CO was conducted through the Vienna ab initio Simulation Package (VASP) with the projector augment wave method [−5 eV and 0.02 eV Å−1, respectively. A vacuum layer of 15 Å was constructed to eliminate interactions between periodic structures of the surface models. The van der Waals interaction was amended by the zero damping DFT-D3 method of Grimme [The theoretical simulations were conducted via the Materials Studio  equipped with the CASTEP mode. Also, we utilized the Perdew–Burke–Ernzerhof (PBE) form exchange-correlation functional within the generalized gradient approximation (GGA). The structures of the (001) plane of ZIS1 and ZIS4 were optimized. The formation energy barrier of He method . A generf Grimme . The Gibf Grimme .mIn2S3+m on simultaneous photocatalytic CO2 reduction and selective BA oxidation. By adjusting the element composition, the band gap energy (Eg) of ZnmIn2Sm+3 could be controlled, resulting in adjustable redox ability. The CO2 reduction activity and selectivity of BA oxidation products were found to be influenced by the Zn/In ratio in ZIS. Specifically, ZIS4 exhibited higher CO2 adsorption capacity and lower CO2 activation, while ZIS1 had a higher energy barrier for H2 evolution. The presence of both a CO2 atmosphere and a BA solution was crucial for achieving a high generation rate of CO and C-C coupling products. Moreover, the formation rate of BAD decreased with increasing Zn/In ratio, while the formation rates of hydrogenation products, HB and BZ, increased and reached their highest values at ZIS3. The selectivity of BAD decreased from ZIS1 to ZIS4, while the selectivity of HB increased. The yield of BAD decreased, while the yield of HB and BZ increased with increasing Zn/In ratio. These results highlight the potential of adjusting both the H2/CO ratio and the oxidation products of BA by altering the Zn/In ratio in ZIS. Overall, this study provides valuable insights into the role of the Zn/In ratio in the simultaneous photocatalytic CO2 reduction and selective BA oxidation process.In summary, this study investigated the effects of composition faults in Zn


These data show a broader chemokine binding repertoire of GPR182 than previously reported and they will be important for future work exploring the physiological and pathophysiological roles of GPR182, which we propose to be renamed atypical chemokine receptor 5 (ACKR5).Atypical chemokine receptors (ACKRs) play pivotal roles in immune regulation by binding chemokines and regulating their spatial distribution without inducing G-protein activation. Recently, GPR182, provisionally named ACKR5, was identified as a novel ACKR expressed in microvascular and lymphatic endothelial cells, with functions in hematopoietic stem cell homeostasis. Here, we comprehensively investigated the chemokine binding profile of human and mouse GPR182. Competitive binding assays using flow cytometry revealed that besides CXCL10, CXCL12 and CXCL13, also human and mouse CXCL11, CXCL14 and CCL25, as well as human CCL1, CCL11, CCL19, CCL26, XCL1 and mouse CCL22, CCL24, CCL27 and CCL28 bind with an affinity of less than 100 nM to GPR182. In line with the binding affinity observed  Atypical chemokine receptors (ACKRs) bind chemokines but do not lead to G-protein activation and subsequent cellular effects. Instead, they recruit β-arrestin, which promotes chemokine uptake and scavenging to remove chemokines from the extracellular space and to limit the spatial availability of the chemokines . There aHEK-293 cells stably expressing human GPR182 or mouse GPR182 were generated by lentiviral transduction followed by puromycin selection.2, 2.56 mM CaCl2, 25 mM Hepes (pH 7.4)). CXCL10-AF647 was added to the cells and cells were then incubated for 1 h under gentle shaking at 4°C to avoid receptor internalization. Thereafter, cells were washed twice with binding buffer and fixed for 10 min with 1% PFA diluted in binding buffer on ice. After centrifugation, cells were resuspended in binding buffer and the binding of CXCL10-AF647 to the cells was determined by flow cytometry (BD FACS Canto II) after addition of DAPI to exclude dead cells.Equilibrium binding of AlexaFluor-647 labelled human CXCL10  to human and mouse GPR182 was performed in single cell suspensions obtained by trypsin/EDTA treatment of cultured parental HEK-293 cells or HEK-293 cells stably expressing human or mouse GPR182. Cells were resuspended in cold (4 °C) binding buffer  and a high (1 µM) ligand concentration using AlexaFluor-647 labelled human CXCL10 at a concentration of 50 nM . Human Cectively   were human CXCL12a, CXCL12b and CXCL13 as well as mouse CXCL12a, CXCL12b, CXCL11 and CCL28 (i = 10–100 nM) were human CXCL10, CXCL11, CCL1, CCL11, CCL19, CCL25, CCL26, XCL1 and mouse CXCL13, CXCL14, CCL22, CCL24, CCL25 and CCL27. In the group of low-affinity binding chemokines (Ki = 100–300 nM) were human CXCL3, CXCL9, CXCL14, CXCL16, CCL28 and mouse CXCL9, CXCL10 and CCL11 . We found that, in addition to CXCL10, CCL12 and CXCL13  or low affinity (100–300 nM) , 4 Our din vitro results that mouse CCL19 does not bind mouse GPR182.We also determined in GPR182 deficient mice the serum levels of several chemokines that we have identified to bind mouse GPR182. We found that not only serum levels of CXCL10, CXCL12 and CXCL13 , but alsIn conclusion, these data define the spectrum of chemokines interacting with the atypical chemokine receptor GPR182 and show that GPR182 binds more than a third of the human and murine chemokines with an affinity between 2 and 300 nM and with some species specificities . Future


We also demonstrate that AcrIIIB2 interacts with Cmr4α subunit, forming a complex with target RNA and Cmr-α ribonucleoprotein complex (RNP). Furtherly, we discover that AcrIIIB2 inhibits the RNase activity, ssDNase activity and cOA synthesis activity of Cmr-α RNP in vitro under a higher target RNA-to-Cmr-α RNP ratio and has no effect on Cmr-α activities at the target RNA-to-Cmr-α RNP ratio of 1. Our results suggest that once the target RNA is cleaved by Cmr-α RNP, AcrIIIB2 probably inhibits the disassociation of cleaved target RNA, therefore blocking the access of other target RNA substrates. Together, our findings highlight the multiple functions of a novel anti-CRISPR protein on inhibition of the most complicated CRISPR–Cas system targeting the genes involved in the whole life cycle of viruses.CRISPR–Cas systems are widespread in prokaryotes and provide adaptive immune against viral infection. Viruses encode a type of proteins called anti-CRISPR to evade the immunity. Here, we identify an archaeal virus-encoded anti-CRISPR protein, AcrIIIB2, that inhibits Type III-B immunity. We find that AcrIIIB2 inhibits Type III-B CRISPR–Cas immunity   Bacteria and archaea have evolved multiple immune systems including the well-studied CRISPR–Cas systems ,2 to preMGEs have evolved diverse strategies to defend against these antiviral systems. Among them, point mutations at CRISPR–Cas targeted sites  and the Two Acr families (AcrIII1 and AcrIIIB1) have been identified to defend against Type III CRISPR–Cas systems ,28. AcrISulfolobus virus SIRV3-encoded anti-CRISPR protein and designated it as AcrIIIB2, which is the first Acr identified to inhibit Type III-B immunity targeting both viral early-expressed and middle-/late-expressed genes. We revealed that AcrIIIB2 interacts with Cmr4α subunit to form a complex with target RNA and Cmr-α RNP, preventing dissociation of target RNA from the Cmr-α complex, thereby shutting down the turnover of the complex to inactivate RNase, ssDNase and cOA synthesis activities of Cmr-α RNP.Here, we identified a E. coli, the coding sequence of AcrIIIB2 (BHS13_gp40) was amplified from the genomic DNA of SIRV3 (Sulfolobus islandicus Rod-Shaped Virus 3) by PCR using the primers listed in SIRE_RS04505), Cmr4α (SIRE_RS04485), Cmr5α (SIRE_RS04490) and Csx1 (SIRE_RS04455) were amplified from the genomic DNA of S. islandicus REY15A by PCR using the primers listed in cmr4α gene fragment was inserted into pET30a between the Nde I and Sal I restriction sites to generate C-terminal 6 × His-tagged Cmr4α. The cmr4α gene fragment was inserted into pACYCDuet-1 between the Nde I and Xho I restriction sites to generate C-terminal 6× His-tagged Cmr4α. The cmr5α and csx1 gene fragments were inserted into pET30a between the Nde I and Xho I restriction sites. The cmr5α gene fragment was inserted into pACYC_Duet-1 between the Nde I and Xho I restriction sites to generate C-terminal 6× His-tagged Cmr5α. The cmr2α gene fragment was inserted into pMAL-C5X-His between the Nde I and EcoR I restriction sites, such that the encoded proteins have a C-terminal 6× His tag and an N-terminal MBP tag. The csx1 gene fragment was inserted into pET30a between the Nde I and Xho I restriction sites to generate C-terminal 6× His-tagged Csx1. The csx1 gene fragment was inserted into pACYC_Duet-1 between the Nde I and Xho I restriction sites to generate C-terminal 6× His-tagged Csx1. All the primers were synthesized by Sangon Biotech . All the plasmids were confirmed by sequencing before transformation and then transformed to E. coli BL21 (DE3) to obtain corresponding strains. The strains are listed in To express the proteins in BHS13_gp06, BHS13_gp39 and BHS13_gp40 were inserted in pAC-SS1, between Nde I and Nhe I, respectively (S. islandicus E233S1 cultivation and transformation were described previously (The pAC-SS1 was used to construct a series of interference plasmids. The expression cassette of ectively . The plaeviously . All theE. coli BL21 (DE3), the strains carrying the indicated plasmids were grown in LB medium containing the corresponding antibiotics. At an optical density optical density at 600 nm (OD600) of ∼1.0, protein expression was induced with 0.1 mM isopropyl-β-d-thiogalactopyranoside (IPTG) at 18°C for 18 h. Then, the cells were collected by centrifugation at 7000g for 10 min. The cell mass was resuspended in 50 ml of lysis buffer  and stored at −80°C until protein purification. To prepare cell extracts, the cells were disrupted by French press and the lysate was subjected to centrifugation at 13 000g for 40 min to remove cell debris. Then, the cell extract was loaded onto Ni-NTA agarose resin columns . After the column was washed with lysis buffer containing 60 mM imidazole, His-tagged proteins were eluted using a lysis buffer containing 300 mM imidazole. Then, the elution fractions were concentrated employing an Amiconultra centrifugal filter with corresponding cutoff  and then diluted for 30-fold with Buffer A . The diluted samples were loaded onto a 5 ml HiTrap Q HP column  and the proteins were eluted using a 35 ml linear gradient of 0–1 M NaCl. The fractions containing target proteins were concentrated again and loaded onto a Superdex 200 Increase 10/300 GL column . Finally, the proteins were eluted with Buffer C  and analyzed by sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS–PAGE). His-tagged Csx1 was purified in a similar way except the strains were grown in ZYP-5052 medium for auto-induction . After the column was washed with binding buffer, GST-tagged proteins were eluted using an elution buffer . Then, the elution fractions were concentrated employing an Amiconultra centrifugal filter with corresponding cutoff  and samples were loaded onto a 5 ml HiTrap Desalting column . Finally, the proteins were eluted with Buffer C  and analyzed by SDS–PAGE.600 reached 0.8–1.0. Expression was induced by adding IPTG to a final concentration of 0.5 mM at 16°C overnight. Cells were harvested by centrifugation (7000g for 10 min) and lysed by high-pressure homogeniser (800 bar) in buffer D  glycerol, 20 mM imidazole and 1 M NaCl). The lysate was centrifuged at 13 000g for 60 min at 4°C, and the supernatant was applied onto the Ni-NTA column  pre-equilibrated with buffer D. After washing with 20 column volumes of buffer D, the Ni-NTA column was washed at room temperature with 10 column volumes of buffer E  to remove the nucleic acids retained by the AcrIIIB2, followed by 5 volumes of buffer D. The protein was eluted with buffer F  glycerol and 300 mM imidazole). Then, the elution fractions were concentrated employing an Amiconultra centrifugal filter with corresponding cutoff  and loaded onto a Superdex 200 Increase 10/300 GL column  pre-equilibrated with buffer G  glycerol). Eluted proteins were incubated with SUMO-protease at 4°C overnight. After cleavage, the samples were incubated at 70°C for 20 min to remove SUMO protease. The His-6 -SUMO-tag cleaved AcrIIIB2 was further purified by Ni-NTA resin (QIAGEN) equilibrated with buffer G  glycerol), the flow through fractions were pooled, concentrated by ultrafiltration and then snap-frozen in liquid nitrogen for later usage.To obtain nucleic acid-free AcrIIIB2, cell culture carrying pET28a-SUMO-AcrIIIB2 was grown in LB medium at 37°C until the ODThe MBP-tagged AcrIIIB2 was purified using high salt buffer (buffer D to buffer F) to remove nucleic acids and further purified using Superdex 200 Increase 10/300 GL column  pre-equilibrated with buffer G  glycerol).S. islandicus strains carrying a cmr6α expression plasmid were grown in SCV at 78°C up to OD600 = 0.7, and cells were collected from at least 12 l of culture by centrifugation at 8000g for 10 min. The cell pellet was re-suspended in Buffer I  and disrupted by a French press. The cell extract was loaded onto a 1 ml HisTrap HP  and His-tagged protein was eluted by Buffer J . Five milliliters of Buffer B fractions were concentrated and further purified by size exclusion chromatography in Buffer K  with a Superdex 200 Increase 10/300 GL column . Sample fractions were analyzed by SDS–PAGE and those containing the complete set of Cmr–α components were pooled together and used for further analysis.The Cmr-α RNP was expressed as described before . S. islad-galactopyranoside) method as described previously (600 = 0.2–0.3) were collected and re-suspended in 10 Mm Tris-HCl, pH 8.0. The cell suspensions were sonicated to yield crude cellular extracts. After removing cell debris by centrifugation at 13 000g and 4°C for 30 min), the cell lysates were suitable for ONPG assay. Protein contents of the cellular extracts were determined using Micro BCA Protein Assay Kit (Pierce). Samples were either assayed immediately or stored at −80°C. For each assay, 10–50 μl of supernatant was transferred to a microcentrifuge tube containing 450–490 μl of reaction buffer with 2.8 mM ONPG and 50 mM sodium phosphate, pH 6.5, in a total volume of 500 μl. Samples were incubated at 75°C for 10 min and the reaction was stopped by adding an equal volume of 1 M sodium carbonate. Yields of 4-nitrophenol were determined by measuring at 420 nm using Nanodrop1000 Spectrophotometers. One specific unit was defined as 1 mmol 4-nitrophenol produced per min per mg total protein.β-glycosidase assay was carried out using ONPG  analysis were extracted using TRIzol® (Invitrogen) according to the manufacturer's instructions. Then, 1 μg RNA was used for generating complementary DNA (cDNA) with the HiScript® II Q RT SuperMix for qPCR (+gDNA wiper)  using random primer in a 10-μl volume. Two primer sets, Qtarget and Qref that were designed for amplification of PCR products in the target region or in a reference region of the mRNA, respectively, were employed for PCR amplification using Taq Pro Universal SYBR qPCR Master Mix  and a QuantStudio 5 Real-Time PCR System (Applied Biosystem) with the following PCR condition: denaturing at 95°C for 5 min, 40 cycles of 95°C for 15 s, 60°C for 20 s and 72°C for 20 s. The amount of uncut mRNA is expressed as the ratio between the amount of S1 RNA protospacer in pAC-SS1-Virus gene transformants and that in the corresponding pAC-SS1 and pSeSD1 transformants.S. islandicus ΔC1C2 , the cells were removed by centrifugation at 8000g for 10 min and the virus particles in the supernatant were concentrated by ultrafiltration using 1 000 000 molecular-weight-cutoff Amicon ultra centrifugal filter . The concentrated virus particles were then dissolved in viral storage buffer containing 20 mM Tris-HCl, pH 7.0, 20% glycerol and stored at 4°C before use.A sensitive strain, us ΔC1C2 , was groS. islandicus ΔC1C2 culture (OD600 around 0.4). The mixture was preheated at 75°C and further mixed with an equal volume of preheated 0.4% GELRITE . Then, the mixture was spread onto pre-warmed SCVU plates. Plaques were counted after the plates had been incubated at 75°C for 2 days.SCVU plates were prepared before the assay. To determine viral titer in the storage buffer, the storage buffer was serially diluted and mixed with 4 ml of fresh S. islandicus ΔC1C2 culture (OD600 around 0.4) and 4 ml of preheated 0.4% GELRITE and 100 μl of Mg2+/Ca2+ onto SCVU plates. Then, cells were removed from the SMV1-infected cultures and the supernatant was serially diluted. Then, 10 μl of the diluted supernatant (from 10−1 to 10−6) was dropped on the ΔC1C2 plates. Pictures of the plates were taken at corresponding time.To perform the drop plaque assay, ΔC1C2 plates were firstly prepared by spreading the mixture of 4 ml of preheated 600 of ∼0.1, 50 ml of the cultures were infected with SMV1 at indicated MOI. The MOI was calculated based on the estimation that 1 ml of OD600 = 0.1 culture contains 1 × 108 cells. At indicated time points, samples were removed from the cultures for analysis.The strains were grown at exponential phase for at least 72 h. At an OD2, 1 mM dithiothreitol, pH 6.0). The reaction was performed at 70°C and stopped at the indicated time point by the addition of 2× RNA loading dye (NEB) and cooling on ice. Finally, the samples were heated for 5 min at 95°C and separated on denaturing polyacrylamide gels (18% polyacrylamide) and visualized by fluorescence imaging using a Typhoon FLA 7000 laser scanner . For ssDNA cleavage assay in Figure 2, 1 mM dithiothreitol, pH 6.0). The reaction was performed at 70°C and the reaction was taken out and kept on ice at the indicated time point, reactions were stopped by adding 1 μl of 6 M guanidinium thiocyanate and 10 μl of 2× RNA loading dye (NEB). The samples were heated for 5 min at 95°C and separated on 18% denaturing polyacrylamide gels and visualized by fluorescence imaging. For AcrIIIB2-His protein related cleavage assays, the reaction performed the same except the amount of AcrIIIB2-His added.RNA and ssDNA cleavage assays performed with Cmr-α RNP were conducted as described previously . RNA cleQuantification analysis of the RNA and ssDNA cleavage assays were performed with ImageJ as described previously .in vitro pull-down assay, His-tagged Cmr-α complex, Cmr4α, Cmr5α, Csx1, MBP or MBP-Cmr2α-His was incubated with GST-tagged AcrIIIB2 and GST, respectively, in 500 μl of assay buffer  at 4°C for 6 h. The proteins were then mixed with 50 μl of Ni SepharoseTM 6 Fast Flow (Cytiva) with constant rotation at 4°C for 1 h. The beads were then washed thrice with assay buffer containing 20 mM imidazole. Subsequently, beads were boiled in loading buffer and the pulled-down protein complexes were separated on 15% SDS–PAGE.For the in vivo pull-down assay, for co-purification of His-tagged Cmr4α, Cmr5α or Csx1 and non-tagged AcrIIIB2, plasmids expressing Csx1 and AcrIIIB2 were transformed into E. coli BL21(DE3) cells, which were cultured in 500 ml of LB medium containing 25 μg/ml chloramphenicol at 37°C for 3 h to an OD600 of 0.6–0.7, and then induced with 0.1 mM IPTG for 16 h at 12°C. The cells were harvested and resuspended, then lysed by ultrasonication. Supernatant was collected after centrifugation and filtrated with 0.22-μm filter. The filtered supernatant was loaded onto a Ni-NTA agarose column. The column was washed with 10 volumes of elution buffer  and protein eluted by gradient imidazole solution. Samples collected at each step were analysis by SDS–PAGE.For the Proteins from SDS–PAGE gels were transferred onto a PVDF membrane  using Trans-Blot SD Semi-Dry Transfer Cell . The membrane was blocked in TBST buffer  containing 6% milk, followed by incubation with anti-GST serum. On completion of three consecutive washing steps, the membrane was incubated with the secondary antibody (Goat Anti-Mouse IgG) . After removing unspecific binding, the Clarity Western ECL Substrate  was dropped onto the membrane and the signals were recorded using Tanon 5200 .To analyze the nucleic acid affinity of AcrIIIB2 and effects of AcrIIIB2, four different FAM labeled RNA substrates  and one FAM labeled ssDNA substrate (ssDNA1) were incubated with His-tagged AcrIIIB2, respectively, in a 10-μl mixture at 70°C for 5 min. The incubation buffer contained 20 mM Mes pH 6.0, 10 mM EDTA. The sequences of the substrates are listed in To analyze the effect of AcrIIIB2 on the interaction between Cmr-α RNP and the target-RNA, 25 nM Cmr-α RNP, indicated concentrations of AcrIIIB2 were incubated with 250 nM RNA1 in the electrophoretic mobility shift assay (EMSA) buffer at 70°C for 10 min. Last, the samples were analyzed by native PAGE and visualized with a Fujifilm scanner.32P labeled ATP substrates. Then, the α-cOAs and Csx1 were incubated at 70°C for 5 min with or without AcrIIIB2 addition, and the reactions were stopped by addition of 2× RNA loading dye. After cooling on ice for 5 min, all samples were separated on 10% native PAGE. Labeled products were detected by exposing the gel to a phosphor screen and scanned with a Fujifilm scanner (FLA-5100).To detect the effect of AcrIIIB2 on the binding between cOAs and Csx1 protein, we synthesized the α-cOAs using the α-32P labeled ATP by Cmr-α RNP were conducted as previously described .Biochemical assays for testing cOA synthesis from α-escribed . To deteVisualization of genomic comparison was done with EasyFig .Sulfolobus virus SIRV3, SIRV1 (acr) genes , which were located near the two putative Acr-associated-genes (aca) BHS13_ gp01 and BHS13_ gp45  and mRNA level , indicating the inhibition effect of the gp06- and gp40-encoded proteins on Type III-B RNA interference activity  the β-galactosidase activity . We obtained similar results that expression of gp40 gene showed significantly inhibitory effect on Type III-B Cmr-α module but expression of gp06 gene did not  were infected by SMV1 at a multiplicity of infection (MOI) of ∼2, using ΔC1C2 strain that lacks any CRISPR–Cas immunity as the control strain. Cultures containing pTSMV1_36 showed the same growth state with or without viral infection, while cultures containing pTSMV1_36OE40 and control strain ΔC1C2 displayed significant growth retardation after viral infection  and middle-/late-expressed genes (CF87_ gp04 and CF87_ gp38) of SMV1. Both interference plasmids and that carrying acrIIIB2 gene expression cassette were transformed into Cmr-α strain and the transformant cultures were infected by SMV1 at a MOI of ∼2. Without SMV1 infection, the cultures in presence or absence of acrIIIB2 gene showed the same growth curves compared with the ΔC1C2 control cultures in SCV medium . Our pull-down data showed that GST-AcrIIIB2 was co-purified with His-tagged Cmr-α RNP by Ni-NTA beads, while GST as the control was not co-purified Figure . Westernic acids . To exclic acids  in fractic acids . MBP-tagic acids . To confmidazole , which idirectly . The HD directly . The in AcrIIIB2 .E. coli, which suggests the RNA binding activity of AcrIIIB2 is non-specific. Then, we confirmed that AcrIIIB2 bound different RNA substrates -encoded AcrIIIB1 binds the Cmr RNPs (Cmr-α and Cmr-γ) to inhibit the type III-B CRISPR–Cas immunity system from targeting middle/late viral genes rather than early genes  have been characterized for Type III systems. These two Acrs inhibit TypeIII CRISPR–Cas immunity system programmed to only target the middle/late genes by interfering with the activity of Type III-associated ribonucleases ,28. Sulfly genes . The cA4ly genes ,51–52, tly genes . Therefoly genes . HoweverIn this study, we identified a virus-encoded novel anti-CRISPR (AcrIIIB2) that inhibits Type III-B CRISPR–Cas immunity regardless of viral early or middle/late gene to be targeted. AcrIIIB2 is the first identified Acr inactivates Type III immunity against viral early expressed gene that could greatly enhance virus survival. We proposed a model Figure  for the in vitro (Figure Sulfolobus islandicus REY15A (The cOAs-activated collateral RNase activity of Csm6/Csx1 plays an important role in targeting middle/late-expressed viral genes in Type III system ,45. Howeo Figure . Howevero Figure . Althougs REY15A ,53–55.et al. in a preprint article (Sulfolobus virus SIRV3 with its homolog undetected, our finding infers that more unknown Acrs against Type III CRISPR–Cas systems are probably encoded by the mobile genetic elements and even their hosts. Exploring these unknown Acrs will expand our understanding of the competition between CRISPR–Cas and anti-CRISPRs and could also raise the genetic tools to control CRISPR–Cas systems in diverse applications (It is worth noting that the inhibition of Cmr-α turnover by AcrIIIB2 and the detailed mechanism behind the inhibition were first reported by Lin  article , and ourications , includiications ,59 and Rications . In summgkad804_Supplemental_FileClick here for additional data file.


However, the unsupported metal oxide catalysts (such as α-Fe2O3) that would be suited for this purpose exhibit poor performance in TCMD. To overcome this issue, a novel strategy was developed as a part of this work, whereby oxygen vacancies (OVs) were introduced into unsupported α-Fe2O3 nanoparticles (NPs). Systematic characterization of the obtained materials through analytical techniques demonstrated that mesoporous nanostructured unsupported α-Fe2O3 with abundant oxygen vacancies (OV-rich α-Fe2O3 NPs) could be obtained by direct thermal decomposition of ferric nitrate at different calcination temperatures  under ambient conditions. The thermocatalytic activity of the resulting OV-rich α-Fe2O3 NPs was assessed by evaluating the methane conversion, hydrogen formation rate, and amount of carbon deposited. The TCMD results revealed that 900 °C was the most optimal calcination temperature, as it led to the highest methane conversion (22.5%) and hydrogen formation rate (47.0 × 10−5 mol H2 g−1 min−1) after 480 min. This outstanding thermocatalytic performance of OV-rich α-Fe2O3 NPs is attributed to the presence of abundant OVs on their surfaces, thus providing effective active sites for methane decomposition. Moreover, the proposed strategy can be cost-effectively scaled up for industrial applications, whereby unsupported metal oxide NPs can be employed for energy-efficient thermocatalytic CH4 decomposition into hydrogen fuel and carbon nanomaterials.Thermocatalytic methane decomposition (TCMD) involving metal oxides is a more environmentally friendly and cost-effective strategy for scalable hydrogen fuel production compared to traditional methane steam reforming (MSR), as it requires less energy and produces fewer CO/CO The available evidence indicates that electricity can be efficiently obtained from hydrogen-based sources without any environmental pollution ,2,3,4. Hmissions ,6,7. Thu process ,9,10.2 emission rate is lower than in MSR, it can be economically scaled up for practical industrial applications, including biomethane exploitation for carbon generation and storage [2O3 and MgO or other metal oxides, which serve as supporting materials. Although Ni and Co particles are characterized by high activity in the 500−700 °C temperature range and their use results in a high graphitic carbon growth rate [To overcome the aforementioned challenges inherent in currently used techniques, thermocatalytic methane decomposition (TCMD) based on metal oxide catalysts can be adopted, as it is cleaner and more cost-effective ,11,12. A storage ,14. In cwth rate ,12, Ni- wth rate ,16,17.2 and carbon materials while benefiting from their non-toxic nature, wide availability, and high activity [2O3) can be utilized for this purpose, as it is the most thermodynamically stable iron oxide under ambient conditions and is relatively inexpensive, readily available, and environmentally safe. However, to facilitate the separation and recovery of catalysts and carbon products, magnetic unsupported solid metal catalysts are usually used; however, unsupported α-Fe2O3 catalysts currently have poor methane decomposition performance. To overcome this issue, various strategies have been proposed, including morphological control [Therefore, Fe-based catalysts could be used for TCMD to produce Hactivity ,19. In p control ,21, elem control , heteroj control ,23, and  control ,25. In t control ,27. Exta control ,29.2O3 nanoparticles (NPs) for thermocatalytic methane decomposition without the use of any supporting agents is proposed. Specifically, oxygen vacancies are introduced into unsupported α-Fe2O3 NPs, making them suitable for TCMD. The catalyst is prepared via the calcination method at temperatures  under ambient conditions. During the calcination process, OVs are created on the surface of the unsupported α-Fe2O3 NPs. Thus, this one-step, highly efficient, and controllable method is highly cost-effective and scalable. In the sections that follow, we report on the preparation, characterization, and catalytic performance of mesoporous nanostructured unsupported α-Fe2O3 with abundant oxygen vacancies (OV-rich α-Fe2O3 NPs), which were used for efficient thermocatalytic methane conversion to hydrogen and carbon nanomaterials.In practical applications, methane decomposition catalysts for hydrogen production are generally synthesized and/or prepared through impregnation, co-precipitation, and sol-gel processes. However, when a two-step preparation is conducted, catalyst morphology cannot be adequately controlled, and its structure changes with the addition of metals, thus affecting the particle distribution and size. Therefore, in this work, a novel method for the development of unsupported α-Fe2O3 NPs were prepared via thermal decomposition of ferric nitrate nonahydrate Fe(NO3)3.9H2O  at different temperatures. In the typical procedure, 5 g of Fe(NO3)3.9H2O  was calcinated at 500, 700, 900, and 1100 °C in ambient air for 5 h (5 h) to obtain samples denoted as FeN-500 °C, FeN-700 °C, FeN-900 °C, and FeN-1100 °C, respectively as indicated in 2O3 NPs were obtained by cooling the as-prepared samples to room temperature.OV-rich α-Fe2O3 NPs and spent samples collected after use for TCMD were studied via X-ray diffraction (XRD) analysis over the 2θ = 10−70° scanning range, using the X-ray diffractometer , Cu Kα radiation (λ = 1.5406 A). The surface morphology of the obtained fresh OV-rich α-Fe2O3 NPs and spent samples were observed using a scanning electron microscope , while the textural properties of the fresh samples, including surface area, pore volume, and pore radius, were measured using N2 physisorption isotherms using a Quantachrome Autosorb IQ model ASIQA3V600000–6 instrument. X-ray photoelectron spectroscopy (XPS) was further employed to investigate the near-surface chemical composition and oxidation states of the studied materials. A Thermo K Alpha spectrometer operating at 1486.6 eV with a 400 μm spot size and charge correction was utilized for this purpose. As an internal standard, all binding energy estimates were calibrated to the C 1s energy (284.5 eV). In addition, thermogravimetric analyses (TGA) were carried out in ambient air using a Netzsch proteus 70 instrument at 10 °C/min increments within the 25–1000 °C temperature range. Collected TGA data demonstrated typical mass loss with regard to temperature, and their corresponding first derivative thermogravimetric (DTG) graphs provided information on mass loss rate versus temperature.For crystalline phase identification, the obtained fresh OV-rich α-Fe2O3 NPs was investigated in a quartz tubular fixed-bed reactor with a 1.5 cm internal diameter and 50 cm total length. For this purpose, 0.5 g of the previously prepared fresh catalyst sample was placed in the center of the tube between the ceramic fiber plugs preheated to 800 °C. Next, a 3:1 mixture of CH4 and N2 feed gas (supplied by AHG at 99.99% purity) was introduced into the reactor at a 20 mL/min flow rate, which was controlled by a mass gas flowmeter (MKS PR4000B). During data analysis, the nitrogen present in the mixture was used as the internal standard. The OV-rich α-Fe2O3 NPs were not subjected to any pretreatment because methane is considered a reductant. Reaction products were examined using online Gas Chromatography, on an Agilent GC Model 7890B equipped with 19043 Restek Micro packed GC Columns , while a thermal conductivity detector was utilized to analyze the output gas and determine the hydrogen, nitrogen, and unreacted methane content.The activity of unsupported nanostructured OV-rich α-Fe2O3 NPs through the calcination of pure ferric nitrate nonahydrate (Fe(NO3)3·9H2O) at different temperatures  under ambient conditions is an important aspect of this study, as it allows for the tailoring of the properties of the resulting NPs to optimize their catalytic performance in thermocatalytic methane decomposition.The synthesis of OV-rich α-Fe2O3 NPs remained constant at different calcination temperatures, as demonstrated in the inset of Interestingly, we observed that the mass of the obtained OV-rich α-Fe2O3 NPs that can be obtained is not limited by the calcination temperature. Therefore, this synthesis method can be easily scaled up to produce large quantities of OV-rich α-Fe2O3 NPs for industrial applications, such as energy-efficient thermocatalytic methane decomposition into hydrogen fuel and carbon nanomaterials.This observation is crucial for the scalability of the synthesis process, as it indicates that the amount of OV-rich α-Fe3)3·9H2O under ambient conditions, demonstrating two distinct mass loss regions. These regions indicate that the decomposition of Fe(NO3)3·9H2O salt into Fe2O3 occurs in two main steps. The first step occurring between 75 and 150 °C could be attributed to the removal of the crystalline water bound to the salt and the decomposition of the nitrates within the salt, which corresponds to the formation of ferric oxyhydroxide (FeOOH). The second step, occurring between 150 and 300 °C, indicates the formation of Fe2O3 [2O3 when increasing the calcination temperature from 500 °C to 1100 °C at ambient conditions, as shown in Furthermore, a slight decrease observed before the temperature of 75 °C could potentially be attributed to the loss of adsorbed water weight. The loss of weight corresponding to the removal of adsorbed water from the precursor salt typically begins between 45 and 70 °C, which agrees with our results in 2O3 NPs at different calcination temperatures, and the obtained diffraction patterns are shown in XRD was employed to examine the crystalline structure and determine the phase purity of the obtained OV-rich α-Fe2O3 (PDF Number 33-0664) [3)3.9H2O has completely decomposed to the α-Fe2O3 hematite phase. 2O3. The calcination process at 900 and 1100 °C results in a slight decrease in crystallinity of the formed hematite phase, which is attributed to the sintering of the nanoparticles at these temperatures, which may lead to the formation of defects [The diffraction peaks that can be observed in the XRD patterns are centered at the 2θ = 24.3°, 33.4°, 35.8°, 41.1°, 49.7°, 54.5°, 57.9°, 62.4° and 64.4°, and thus correspond to the (012), (104), (110), (113), (024), (116), (018), (214), and (300) diffraction planes of hematite α-Fe33-0664) . The abs defects .2O3 NPs at different calcination temperatures, and the results are depicted in Scanning electron microscopy (SEM) was employed to examine the morphological features of the obtained OV-rich α-Fe2O3 NPs were measured utilizing N2 adsorption-desorption isotherms and Brunauer-Emmett-Teller (BET)/Barrett-Joyner-Halenda (BJH) analysis, and the findings are presented in 2/g as the calcination temperature increased from 500 to 1100 °C.The textural properties of the OV-rich α-Fe2 adsorption−desorption isotherms of the obtained OV-rich α-Fe2O3 NPs at different calcination temperatures and shows that they are of type IV with H3 hysteresis loop, which is typical of mesoporous hematite α-Fe2O3 [2O3 NPs based on the pore size distribution, which remained in the 19−22 nm range.This trend could be attributed to particle agglomeration associated with elevated temperatures.  α-Fe2O3 . Further α-Fe2O3 . Usually α-Fe2O3 . The isoThus, from the SEM images , it is c2O3 NPs at different calcination temperatures were probed by X-ray photoelectron spectroscopy (XPS), and the findings are shown in 2O3 NPs depicted in 2O3 formation. The O 1s spectra of the OV-rich α-Fe2O3 NPs samples presented in 2O3 , while the signal at the 531.8 eV binding energy corresponds to the hydroxyl group . Interestingly, the peak resulting from the hydroxyl group shifts towards lower energy for the sample that was calcined at 900 °C, which indicates these samples are oxygen-deficient. Thus, the peak O3 at around 531.1 in the FeN-900 °C sample is attributed to the low-coordinated oxygen species adsorbed onto the oxygen vacancies, likely arising from the formation of oxygen vacancies on the NP’s surface. On the other hand, the peaks that appear in the 533–536 eV energy range (labeled as O4) may be related to the surface-adsorbed H2O molecules and carbonate species [1) that appeared at 527.6 eV in FeN-500 °C, FeN-700 °C, and FeN-900 °C samples is attributed to the fact that some of the Fe3+ on the surface can be changed to a low oxidation state such as Fe2+ which is usually associated with the formation of OVs. The OVs are expected to play an important role in the adsorption process, as these vacancy sites can act as initiators for the adsorption of molecules in many surface reactions .The chemical composition and elemental states of the obtained OV-rich α-Fe species ,29,36. F2 peak ascribed to the lattice oxygen in the FeN-900 °C sample is shifted to lower bending energy compared to the other samples, which implies the oxygen vacancies are present in high concentration in this sample.As defect states (such as OVs) are known to appear on the surface of metal oxides at high temperatures, it is clear from 3/2 XPS spectra of the OV-rich α-Fe2O3 NPs obtained in this study. The spectra exhibit five peaks, with two peaks located at 707.6 and 709.7 eV attributed to Fe2+ and the peaks at 712.6 and ~715.4 eV corresponding to the oxidation state of Fe3+. Additionally, a peak at ~720.6 eV can be assigned to the satellite peak, as suggested by previous studies [2+/Fe3+ ratio was calculated to be 0.20, 0.29, 0.36, and 0.22 for samples FeN-500 °C, FeN-700 °C, FeN-900 °C, and FeN-1100 °C, respectively, indicating the formation of OVs. studies ,37,38. T0, suggesting that some Fe3+ was reduced into Fe0, a phenomenon commonly associated with the formation of OVs. The absence of this peak in other samples suggests that the FeN-900 °C sample may contain a higher concentration of OVs. OVs may accelerate the iron oxide reduction process and lead to the formation of more active sites, thereby enhancing catalytic activity.Notably, an additional small peak appeared at 706.2 eV in the FeN-900 °C sample, which is attributed to Fe2O3 NPs at different calcination temperatures were used as catalysts for the TCMD reaction. Their thermocatalytic activities were investigated at a fixed operating temperature of 800 °C and a gas flow rate of (20 mL/min). It should be noted that these materials did not undergo pre-reduction treatment before the reaction. 2O3 NPs at 1100 °C showed the lowest activity, where the highest methane conversions achieved were 9.20%, whereas the highest hydrogen formation rate was 20.80 × 10−5 mol H2 g−1 min−1. In contrast, the prepared OV-rich α-Fe2O3 NPs at 500, 700, and 900 °C displayed higher activity, which can be observed in the initial phase of the reaction, where the maximum methane conversions reached 37.8, 26.1, and 35.2%, respectively, while the maximum hydrogen formation rate was 74.0 × 10−5, 40.3 × 10−5 and 68.2 × 10−5 mol H2 g−1 min−1. It appears that these samples have a partially reducible component that forms active sites, which was followed by a rapid carbon deposit on them, subsequently suppressing their performance. Moreover, after 200 min of TOS, it is noted that the samples of OV-rich α-Fe2O3 NPs showed different activity as there was a gradual increase in their activity, and the order of performance was as follows: the prepared OV-rich α-Fe2O3 NPs at 900 °C > OV-rich α-Fe2O3 NPs at 700 °C > OV-rich α-Fe2O3 NPs at 500 °C > OV-rich α-Fe2O3 NPs at 1100 °C, and the maximum methane conversions achieved were 22.5, 20.6, 18.6, and 9.3%, respectively, whereas the maximum hydrogen formation rate was 47.0 × 10−5, 44.0 × 10−5, 40.7 × 10−5 and 20.83 mol H2 g−1 min−1, respectively.The obtained OV-rich α-Fe2O3, the reaction was carried out under the same conditions, and the amount of catalyst and its iron content were constant, there is a variation in their activities. It appears that the surface area did not play a role in the activity of these materials, as increasing the calcination temperature led to an increase in the particle size and thus a decrease in the surface area, as seen in SEM images in Although these materials have the same phase of α-Fe2O3 NPs surface, which may have played a significant role in the activity of these materials. It is noteworthy that the FeN-500 °C sample at the beginning of the reaction showed a high methane conversion percentage and hydrogen formation rate compared to the FeN-900 °C sample. However, the high activity of FeN-900 °C at the end of the TCMD reaction may be due to the presence of a high concentration of OVs on its surface, as observed in the XPS results in 2O3 NPs surface play an important role in accelerating the iron oxide reduction process compared to those that contain fewer vacancies, which lead to the formation of more active sites during the TCMD, which act as effective active sites for the adsorption of methane. On the other hand, the low catalytic activity of the FeN-1100 °C catalysts can be attributed to the low concentration of the OVs, as is clear from the XPS results of these catalysts, which made them difficult to reduce during the reaction run period as these catalysts were not subjected to a prior reduction process [In an attempt to find the reasons for these disparate activities, it would appear to be due to the presence of defects in the iron oxide composition that arose from the effect of calcination temperatures. The results of XPS analysis  showed t process .2O3 catalysts by our scalable and cost-effective strategy is comparable with previously reported Fe-based catalysts for TCMD, as presented in It is worth mentioning that the activity of the prepared unsupported α-Fe2O3 catalysts at 800 °C, revealing that the previously observed XRD peaks in 2O3 catalysts have almost lost their original structure. It is worth noting that the spent catalysts are denoted as SFeN-500 °C, SFeN-700 °C, SFeN-900 °C, and SFeN-1100 °C. From 2O3 catalysts has changed to Fe0, Fe3C, Fe2O3, and graphite. Two clear peaks can be seen at 2θ = 26° and 2θ = 45° suggesting the formation of graphite carbon and metallic iron, respectively.3C, albeit in small amounts) is confirmed by the peak situated in the 2θ = 38–50° range, and it was suggested that Fe3C species have a catalytic activity for methane decomposition [2O3 phases indicates that the catalysts were not completely reduced due to the carbon deposited on iron, explaining the continuous TCMD up to 480 min as observed in 3C phases in the catalyst component plays a role in the activity of the catalyst [Furthermore, the presence of iron carbide  and hydrogen formation rate (47.0 × 10−5 mol H2 g−1 min−1) after 480 min. Thus, the OV-rich α-Fe2O3 NPs prepared at 900 °C are the most active sample for methane decomposition, and this is due to their possession of abundant oxygen vacancies, which serve as effective active sites for adsorption methane.It is observed from the TGA curves that the weight loss takes place in the range of 500–700 °C due to the combustion of graphitic carbon , which i2O3 NPs at calcination temperatures such as 900 °C possess abundant oxygen vacancies, which would, in turn, increase the number of stable and active sites for the adsorption of methane. It has also been established that the introduction of OVs into the bulk α-Fe2O3 material can weaken the Fe–O bond strength and improve the lattice oxygen mobility, thus catalyzing the reduction of iron oxide to form the active phase for methane decomposition. Therefore, it is reasonable to assume that methane adsorbs on the surface-active sites of the catalyst and reacts with the reducible species, e.g., free Fe2O3 clusters (adjacent Fe3+), surface oxygen species, and defects such as OVs, at the 800 °C reaction temperature. As a result, the C–H bonds on the catalyst surface would be gradually decomposed to generate H2 and nanocarbon materials. Thus, FeN-900 °C, which contains abundant oxygen vacancies, could play an important role in the enhancement of catalytic activity in the thermocatalytic decomposition of methane into hydrogen and nanocarbon materials. A schematic diagram depicting the proposed reaction mechanism of the OV-rich α-Fe2O3 NPs that are used for the thermocatalytic decomposition of methane is illustrated in Available evidence from previous studies indicates that the surface features of catalysts are the main drivers of catalytic methane decomposition. The XPS analysis performed as a part of this work revealed that the obtained OV-rich α-Fe2O3 catalyst by CH4 occurs in three steps, namely Fe2O3 → Fe3O4 → FeO → Fe0. Once Fe0 is formed, it decomposes CH4, which results in the formation of Fe3C, a crucial step in the TCMD process for the formation of nanocarbon materials. The XRD, SEM, and XPS findings obtained in the current investigation indicate that the reduction of the OV-rich α-Fe2O3 catalysts follows the global mechanism (Fe2O3 → Fe0), whereby Fe3C is formed as a result of the reaction of Fe0 with the produced carbon from CH4 decomposition. Therefore, it is clear that Fe0 is an active phase for initializing the TCMD reaction at high temperatures , which suggests that the OV-rich α-Fe2O3 catalysts possess an effective catalytic nature for TCMD for hydrogen and nanocarbon production.Furthermore, based on the results reported in extant studies ,18,19, t2O3 NPs with abundant oxygen vacancies on the surface via the thermal decomposition of ferric nitrate at different temperatures . The obtained OV-rich α-Fe2O3 NPs at different calcination temperatures were employed as catalysts for the thermocatalytic decomposition of methane to produce H2 and nanocarbon. Further investigations confirmed that the introduction of OVs on the as-prepared OV-rich α-Fe2O3 NPs affected the characteristics and thermocatalytic performance of these catalysts. Based on the XPS analysis, the OVs on the OV-rich α-Fe2O3 surface were responsible for the increase in the number of active sites, thus aiding methane absorption. The morphological characterization results revealed that the most commonly obtained spent catalysts were nanosheets, which were the predominant carbon form deposited on the spent catalysts. According to the XRD results, the TCMD reduction follows the Fe2O3 → Fe0 global mechanism. By evaluating the thermocatalytic activity of the obtained OV-rich α-Fe2O3 NPs in terms of TCMD for hydrogen production and nanocarbon formation, it was determined that 900 °C calcination temperature is optimal for producing highly efficient OV-rich α-Fe2O3 NPs, which showed the highest methane conversion (22.5%) and hydrogen production rate (47.0 × 10−5 mol H2 g−1 min−1) after 480 min. Such outstanding thermocatalytic performance of OV-rich α-Fe2O3 NPs is attributed to the presence of abundant OVs on their surfaces, which serve as effective methane adsorption sites.In this study, a scalable and cost-effective one-step approach was developed for obtaining efficient unsupported OV-rich α-Fe