Pex genes-encoded proteins named peroxins (PEX proteins) and single peroxisomal enzyme deficiencies. The PEX11 protein family  plays an important role in peroxisomal proliferation and fission. However, their specific functions and the metabolic impact caused by their deficiencies have not been precisely characterized. To understand the systemic molecular alterations caused by peroxisomal defects, here we utilized untreated peroxisomal biogenesis factor 11α knockout (Pex11α KO) mouse model and performed serial relative-quantitative lipidomic, metabolomic, and proteomic analyses of serum, liver, and heart tissue homogenates. We demonstrated significant specific changes in the abundances of multiple lipid species, polar metabolites, and proteins and dysregulated metabolic pathways in distinct biological specimens of the Pex11α KO adult mice in comparison to the wild type (WT) controls. Overall, the present study reports comprehensive semi-quantitative molecular omics information of the Pex11α KO mice, which might serve in the future as a reference for a better understanding of the roles of Pex11α and underlying pathophysiological mechanisms of peroxisomal biogenesis disorders.Peroxisomes are versatile single membrane-enclosed cytoplasmic organelles, involved in reactive oxygen species (ROS) and lipid metabolism and diverse other metabolic processes. Peroxisomal disorders result from mutations in The online version contains supplementary material available at 10.1007/s00216-021-03860-0. They play a central role in a wide variety of vital metabolic functions, namely (i) β-oxidation of very long-chain fatty acids  and of bioactive secondary lipid mediators (such as prostaglandins and leukotrienes), (ii) α-  and β-oxidation  of branched-chain fatty acids, (iii) biosynthesis of ether-phospholipids , cholesterol, dolichol, and conjugated bile acids, (iv) glyoxylate detoxification, and (v) breakdown of polyamines and purines [oduction .The abundance, size, shape, protein/enzyme composition, and functions of peroxisomes can differ based on the physiological condition and metabolic needs of the cell type, tissue, organ, and/or organism , 4. ReguPex genes  or genes encoding single peroxisomal enzymes  [2O2 metabolism [The functional importance of peroxisomal metabolism for health in humans is emphasized by the existence of numerous peroxisomal disorders. These devastating genetic human diseases are either resulting from mutations in s, PEDs) . In bothtabolism , 8.Pex11 (α and β) knockout mouse models and performed their basal characterization [Pex11 gene (Pex11γ). The three PEX11 protein isoforms  are responsible for peroxisome proliferation and fission by mediating elongation, tubulation, and constriction of pre-existing peroxisomes [Pex11β is expressed constitutively throughout the tissues, whereas α and γ isoforms are tissue specific and pronounced considerably in the heart, liver, and kidney as well as testis [Pex11β, which induces a phenotype similar to Zellweger syndrome and neonatal lethality, mice with a Pex11α KO display a mild phenotype and are viable after birth [Pex11α knockout mice when treated with a high-fat diet develop nonalcoholic fatty liver disease [To study PBDs, Li and Baumgart et al. previously generated and bred rization , 10. Theoxisomes . Pex11β er birth , 10, ena disease .In systems biology, concurrent extraction and investigation of various biomolecules  and integration of mass spectrometry-guided multi-level molecular omics data  of the same sample has become a promising strategy to improve the understanding of complex biological cascades . A seriePex11alpha deficiency, we investigated changes in the lipidome, metabolome, and proteome of different biological specimens  from Pex11α KO adult mice using a liquid–liquid extraction method combined with untargeted sequential omics approaches by ultra-high-performance liquid chromatography equipped with high-resolution tandem mass spectrometry (UHPLC-HRMS/MS). Our study provides extensive semi-quantitative molecular information on the metabolic alterations in Pex11α KO mice, which will complement the understanding of the molecular functions of Pex11α and underlying pathophysiological mechanisms of peroxisomal biogenesis disorders.In order to characterize the metabolic alterations occurring due to 2O), 2-propanol/isopropyl alcohol (IPA), and formic acid were procured from Honeywell Riedel-de Haën . The synthetic lipid internal standards were procured from Avanti Polar Lipids . Sequencing grade modified trypsin was obtained from Promega Corporation  and RapiGest SF surfactant from Waters Corporation . Bradford reagent was purchased from Bio-Rad Laboratories  and ZipTipC18 from Merck Millipore .Ammonium bicarbonate, ammonium formate, bovine serum albumin, dithiothreitol (DTT), iodoacetamide (IAA), methyl tert-butyl ether (MTBE), thiourea, and urea were purchased from Sigma-Aldrich . LC–MS grade solvents acetonitrile (ACN), methanol (MeOH), water  were narcotized using 3% isofluran and sacrificed by cervical dislocation. For the isolation of heart and liver, the animals were perfused with phosphate buffer saline through the left ventricle to remove the blood. Liver and heart tissues were dissected, snap-frozen immediately in liquid nitrogen, and stored at − 80 °C until further processing. Blood was extracted by cardiac puncture immediately following the cervical dislocation and left standing for 30 min at 37 °C to separate the serum from the red blood cells. Then, the samples were spun for 10 min at 1500 × g at 4 °C, and serum was collected and stored at − 80 °C until further use.Pathogen-free C57BL/6 J mice were obtained from the central animal facility of the Justus Liebig University Giessen, Germany. They were kept on a normal laboratory diet and water and maintained under standard environmental conditions. The generation, breeding, and basal characterization of  earlier . Adult 3The animal experiments were performed in accordance with the German Animal Welfare Law and recommendations of institutional animal welfare officers. All experiments were approved by the German Government Commission of Animal Care .Pex11α+/+) and homozygous Pex11α KO (Pex11α−/−) mice were homogenized in phosphate buffer saline solution (200 µl) using a tissue homogenizer  with zirconia beads for 1 min at 20 Hz at 4 °C. 200 µl of liver or heart tissue homogenates and/or 80 µl of serum were transferred into respective glass vials and subjected to liquid–liquid extraction as reported earlier [Ten milligrams of the snap-frozen liver and heart tissues from three biological replicates of WT control ( earlier . Briefly2O buffer (65:30:5 v/v) and analyzed using a hybrid quadrupole orbital trapping mass spectrometer . In brief, 10 µl of resuspended lipid extract were loaded on a reversed-phase ACQUITY UPLC HSS T3  column and separated using a Dionex UltiMate 3000 UHPLC system (Thermo Fisher Scientific), with a flow rate of 250 µl/min. The solvent system consisted of eluent A  and eluent B  both with 10 mM ammonium formate and 0.1% formic acid. Lipids were separated with a 28 min multi-step linear gradient of 30 to 100% eluent B , modified from a previous study [Dried lipid extracts were resuspended in 100 µl of ACN:IPA:Hus study . The optHigh-resolution and accurate mass lipidomic raw datasets were analyzed with LipidSearch (v4.2.23) software (Thermo Fisher Scientific) for identification and alignment , 22. The2, Top10), adopted from a previous study [Dried polar metabolite extracts were resuspended in 100 µl of 15% aqueous methanol and a 10 µl injection volume was used. The separation was performed using a reversed-phase ACQUITY UPLC HSS T3  column at a flow rate of 300 µl/min of a solvent system consisted of eluent A (100% water) and eluent B (100% acetonitrile) both with 0.1% formic acid. Polar metabolites were separated with a 20 min multi-step linear gradient of 1 to 99% eluent B (ESM Table us study . The optPositive- and negative-ion mode polar metabolomic raw datasets were processed independently using the Progenesis QI (v2.4) software (Waters Corporation) with default parameters. The untargeted workflow used for data processing and analysis includes retention time alignment, peak picking, deconvolution, compound annotation, normalization, and relative-quantification . The ionPex11α KO mouse liver and/or heart tissues were solubilized in 50 mM ammonium bicarbonate buffer (50 μl) containing 0.1% RapiGest and denatured at 80 °C for 15 min. Then, the proteins were reduced and alkylated with 100 mM DTT at 56 °C for 30 min, 200 mM IAA at ambient temperature in the dark for 30 min, respectively. After that, the proteins were digested with trypsin (1:20 protease-to-protein ratio) at 37 °C for overnight. The tryptic digestion reaction was stopped by incubating with concentrated formic acid (2 µl) for 10 min at 37 °C. The peptide digests were desalted by ZipTipC18, dried out using vacufuge concentrator, and reconstituted in 3% aqueous ACN with 0.1% formic acid for further MS analysis.Total protein concentrations in supernatants of resuspended pellets were measured with Bradford’s reagent and subjected to in-solution tryptic digestion followed by label-free quantitative bottom-up proteomics experiments as described elsewhere , 25. Bri2, Top10), with slight modifications from our previous study [Peptide digests (2.5 μg) were loaded on a Kinetex C18 reversed-phase  column and separated using a Dionex UltiMate 3000 UHPLC system (Thermo Fisher Scientific), with a flow rate of 250 μl/min. The solvent system consisted of eluent A (100% water) and eluent B (100% acetonitrile) both with 0.1% formic acid. Peptides were separated with a 120 min multi-step linear gradient of 3 to 50% eluent B  using Sequest HT search algorithm. The search was performed with peptide precursor (MS) and fragment (MS/MS) mass tolerance of 10 ppm, 0.02 Da respectively and trypsin as a protease with two missed cleavages and a strict target false discovery rate value of 0.01 (1% FDR). Search criteria also comprised carbamidomethylation (cysteine) as static modification, oxidation (methionine) and acetylation  as dynamic modifications. Unique and razor peptides were considered, precursor abundance values were normalized with total peptide amount, and replicate-based resampling imputed missing values. Abundance ratios were calculated using the pairwise ratio method and significant values were obtained from ANOVA hypothesis test (based on the background population of proteins or peptides). The common external protein contaminant list (MaxQuant database) was used to mark contaminants in the result file. As regulated, only proteins with (i) master group, (ii) high confidence, (iii) at least two peptides, (iv) no contaminants, (v) p-value of ≤ 0.05, and (vi) an abundance ratio of ≤ 0.5 and/or ≥ 2  were considered.Proteomic raw datasets were processed using untargeted label-free processing and consensus quantitative workflow ESM Fig.  of Protet-test , and volcano plots  were employed to select statistically significant lipids and/or polar metabolites. Lipid class levels  represented as mean ± standard deviation and two-tailed Student’s t-test (GraphPad Prism v6.01) were used for statistical comparison between the groups.Integrated chromatographic peak area values of the individual lipids and polar metabolites were exported as a matrix (samples in columns and features in rows) after manual curation, and statistical analyses were performed using freely accessible MetaboAnalyst (v4.0) . LipidomMus musculus” pathway  library, “hypergeometric test” for “over-representation analysis,” and “relative-betweenness centrality” for “pathway topology analysis” were used to identify altered specific metabolic pathways.Differentially abundant lipids and polar metabolites  were combined and explored by metabolic pathway analysis for the identification of altered pathways. The analyses were performed using MetPA module of the MetaboAnalyst (v4.0) . “Mus muProtein analysis through evolutionary relationships  was used to sort proteins with differential abundance into diverse cellular components, molecular functions, biological processes, signalling pathways, and protein classes .Mus musculus were uncovered by employing a hypergeometric test and multiple test correction to attain p-value ≤ 0.05 using the Benjamini–Hochberg FDR correction method inbuilt within the BiNGO plug-in [Gene ontology (GO) clustering analysis for the proteins displaying differential abundance was carried out using STRING  and later visualized in Cytoscape (v3.7.2) BiNGO  . The sig plug-in .Pex11α deficiency, we performed comprehensive semi-quantitative sequential omics analyses of serum, liver, and heart tissue specimens from WT control (Pex11α+/+) and untreated homozygous Pex11α KO (Pex11α−/−) adult mice  are involved in peroxisomal proliferation and division. However, their specific function in these processes and the underlying molecular mechanisms of pathological alterations due to their deficiency have not been completely clarified. To investigate the diverse molecular changes that occur due to 2O liquid–liquid extraction protocol was utilized for the concurrent extraction of lipids (upper organic layer), polar metabolites (lower aqueous layer), and proteins (lower precipitated pellet) [First, we optimized an integrated workflow that can profile a broad spectrum of biomolecules  from a single piece of tissue and/or biological fluids Fig. . Briefly pellet) , 34. Ext pellet) . After eLipids can be identified in positive- and/or negative-ion mode based on their chemical complexity. For instance, the majority of the glycerophospholipids (GP) and sphingolipids (SP) are identified in both ionization modes with various charge carriers, whereas neutral lipids such as monoglyceride (MG), diglyceride (DG), triglyceride (TG), coenzyme (Co), cholesterol, fatty acyl esters of cholesterol (ChE), and carnitine (AcCa) are predominantly observed in positive-ion mode , 37. WitLipidSearch (LS) software, which includes a database of greater than 1.7 million lipids and corresponding predicted fragment ions, was used for the identification and alignment of lipid molecular species based on precursor ion accurate mass and characteristic fragment ion patterns . After i−, resulting from a loss of CO2) requires relatively high collisional energies (NCE ˃ 40) [Even though lipids were identified based on accurate mass (≤ 5 ppm) and fragment ions (≤ 5 ppm), the aligned-results report comprised a huge number of false positives due to various reasons including fragment mismatch, peak tailing, and poor integration of the chromatographic peak. In order to remove/minimize false positives and to provide more confident lipid identifications, a series of pre-defined filtering criteria were applied (ESM Table CE ˃ 40) . MoreoveAfter careful data evaluation and manual curation, a total of 690 (serum), 908 (liver), and 939 (heart) distinct lipid species were retained as unambiguous identifications , and hierarchical clustering analysis , to distinguish between the groups. As seen in ESM Fig. Pex11α KO and WT control mice. This is eventually visualized with two-dimensional hierarchical clustering heatmaps  changes in the abundance (ratio threshold ± 2) of 102 lipid species  in serum, of 145 lipid species  in liver, and 102 lipid species  in heart tissue homogenates of Pex11α KO mice, in comparison to those of WT controls  and Hex1Cer, were found to be common and raised in both the liver tissue and serum. Similarly, 12 and one SM lipid species exhibited higher levels in Pex11α KO mice liver and serum (while three species decreased) in comparison to the WT controls. In contrast, we did not notice statistically significant differences in the individual species and the total sphingolipid class levels of Pex11α KO mouse heart tissues  deficient mice [26:1/0-ceramide lipid and ratio of C26:1/0-ceramide/C22:0-ceramide as possible potential diagnostic markers to study the peroxisomal disorders [Pex1 and Pex26 mutations) [Pex5-mutated Chinese hamster ovary cells [Sphingolipids (SP) are an essential class of bioactive lipids with a sphingoid backbone. They are present as underivatized , or N-acetylated with fatty acids , or further derivatized by addition of charged, neutral, phosphorylated, and glycosylated head groups to form more complex SP . Depending on the fatty acid conjugates and concentration, they play vital roles in proliferation, differentiation, apoptosis, senescence, and autophagy . In the ent mice . Furtherisorders . Likewisisorders  and cultisorders , SM lipiisorders , and certations) . Moreovery cells . Remarkary cells .Pex11α KO mice. Among these, PC lipid showed higher levels in all the tested biological specimens of Pex11α KO mice, whereas PC and PC lipid species exhibited a similar rise in serum and liver, heart and liver tissue homogenates, respectively. Only one lipid species (PC 36:5) in liver, two lipid species including one ether-linked species  in heart, and more interestingly five species  in serum, all comprising poly-unsaturated fatty acids  were significantly decreased in the Pex11α deficient mice. LPC species with a single fatty acyl chain (C ≤ 20), derived from PC lipids, displayed comparatively lower levels in Pex11α deficient animals . In contrast, LPC 14:0 showed slightly higher levels in Pex11α KO mouse heart tissue homogenates. In phosphatidylethanolamine lipid class (the second-most abundant in GP), two species  in serum, one species (PE 32:2) in heart, and six lipid species  in liver were significantly increased in Pex11α KO mice. Similar to PC, PE 36:5 and PUFA containing two species  were significantly decreased in Pex11α KO mouse liver. LysoPE lipids in the liver  followed the same pattern as of LPC but remained relatively constant in serum and heart. A number of PG lipid species (starting from PG 30:0 to 44:10) showed elevated levels in Pex11α KO mouse liver (nine species) and heart (four species) tissue homogenates. Among these, PG  and PG  lipids were found to be common and raised in both the liver and heart tissue homogenates. Nonetheless, individual PG lipid species in serum and total PG and LPG lipid species/class levels in all the tested biological specimens were not significantly changed. In addition to these phospholipid class alterations, we noted significantly increased levels of PI  and PS  lipid species in Pex11α KO mouse liver. On the contrary, three  and two  PI lipid species were decreased in serum and heart tissue homogenates. The remaining glycerophospholipid classes and their individual lipid molecular species did not show major differences in Pex11α deficient animals.Glycerophospholipids (GP) are structural integral components of most cell and organelle membranes, which play crucial roles in various physiological and pathological processes. Within the GP category, we identified several lipid species  spanning 11 different lipid classes , which unveiled a wide diversity of quantitative trends between the tested biological specimens Fig. . In detaPex11α KO mouse liver, possibly due to mitochondrial proliferation [Cardiolipin (CL) is a dimeric phospholipid, which makes up to 20% (inner) and 3% (outer) of the total mitochondrial membrane lipid composition. While in peroxisomes, CL makes up to 2–4% of the total phospholipid pool . In the feration , 10, 49.feration . In thisferation , 51. NevPex11α KO mice. In contrast, DG lipid class levels and a wide variety of individual lipid species (starting from DG 32:3 to 44:9) including several PUFA containing species  were significantly decreased (except DG 38:5) in Pex11α KO mouse liver. However, no statistically significant changes were noted in heart tissues. TG lipids consist of a glycerol backbone esterified with three fatty acids. They are a vital source of energy during cellular metabolism. Among these, 55 TG lipid species  in serum, 14 species  in liver, and 65 lipid species  in heart showed statistically significant differences in Pex11α KO mice when compared to the WT controls. Among the differentially abundant TGs, TG lipid showed reduced levels in all the tested biological specimens of Pex11α KO mice. Likewise, increased levels of TG, and decreased levels of TG and TG lipid species were noted in the liver tissue and serum, whereas lower levels of TG lipid species were observed commonly in serum and heart tissue homogenates. Overall, the majority of the ether-linked and PUFA containing TG lipid species were significantly decreased in Pex11α KO mice (ESM Dataset S1). A minimal number of MG lipid species were identified in serum (one species), heart (three species), and liver (two species) tissue homogenates and they were statistically not as robust as the lipid classes with higher total numbers of species.In the glycerolipid (GL) category, we spotted several lipid species  belonging to MG, DG, and TG lipid classes Fig. . In seruPex11α KO mice. Interestingly, fragmentation data (MS/MS) revealed that the majority of the lipid species with docosahexaenoic acid  moieties were decreased (with few exceptions) in Pex11α deficient mice when compared to those of WT controls  in the biological specimens of Pex11α KO mouse heart tissues. Two cholesteryl ester species  showed relatively lower levels in Pex11α KO mouse serum.In addition to the differences in SP, GP, and GL classes and specific lipid species, other lipid classes including fatty acyl esters of carnitine (AcCa), free and esterified cholesterol (ChE) species, and coenzyme (Co) were confidently identified and relatively quantified in all the tested biological specimens Fig. . ConcisePex1, Pex13, Pex16, and Pex7 mutations) and single PEDs  patients [Pex1, Pex26, and Pex5 mutations) [Pex1 mutation), AMACR and DBP deficiency, Refsum disease, and RCDP type 1 or 5 patients [Several studies employed both targeted and untargeted lipidomics approaches to study the functional consequences and to explore novel molecular biomarkers for a better understanding and diagnosis of peroxisomal disorders. To mention a few, differential lipidomic analyses were carried out in (i) cultured primary skin fibroblasts derived from PBDs  , (iii) ppatients , 59, , and obtained data were evaluated using the Progenesis QI. On average, global metabolomics data generated over 10,000 features across all the tested biological specimens. Putative identification of metabolites was performed for the ions that had MS/MS data. Furthermore, compounds were manually filtered, based on their coefficient of variation, duplicates were removed, and misidentifications based on retention time, quality of peak shape, score, fragmentation match score, isotope similarity, and mass accuracy were deleted. After removal of false positives, by combining both positive- and negative-ion modes data collectively, 123, 98, and 80 metabolites were tentatively identified in serum, liver, and heart tissue homogenates, respectively. The identities of the metabolites  are provided as supplementary Microsoft Excel worksheets  and lipid species  were combined , and metabolic pathways analyses  were performed using the MetPA module of MetaboAnalyst. Several pathways related to lipid metabolism , amino acid metabolism , nucleotide metabolism, carbohydrate metabolism, and other metabolic pathways were found to be altered in Pex11α KO mice. The summary of pathway analysis is shown in Fig. Pex16 and Pex2 mutant Drosophila melanogaster (fruit flies) and Pex5 deficient mouse liver [Using PCA, HCA, and descriptive univariate statistical analysis, we observed a clear separation and significant changes between the ESM Fig. . To explse liver .Fig. 3SPex11α KO mice, tissue protein relative abundance values were compared to those of WT control mice by relative-quantitative proteomics. At this level of the experiment, the remaining lower sediment pellets (possibly containing stable and highly abundant proteins) were re-solubilized, and proteins extracted, digested with trypsin, and analyzed individually  by shotgun label-free quantitative (LFQ) proteomics. Prior to the quantitative proteome data analysis, data quality attributes  and suitability of the sample complexity and applied method  were inspected visually using RawMeat  software  changes in the abundance (ratio threshold ± 2) of 54 proteins  in the liver and 29 proteins  in the heart tissues of Pex11α KO in comparison to the WT control mouse  might be ascribed to the one-step liquid–liquid extraction procedure  optimized for serial-omics analyses, from a single piece of biological sample. Also, the non-appearance of several important peroxisomal membrane proteins, matrix proteins, and peroxins might be ascribed to their low abundance and to the well-known difficulties associated with the extraction of labile hydrophobic proteins.In total, the Proteome Discoverer software with Sequest HT search algorithm identified 1064 and 738 proteins from the sediment pellets of the liver and the heart tissue homogenates, respectively , gene ontology enrichment analysis was carried out using PANTHER and Cytoscape (BiNGO plug-in) bioinformatics tools. Biological information such as molecular functions, biological processes, cellular components, signalling pathways involved, and protein classes of the DAPs was obtained as shown in Fig. Pex11α KO adult male animals. Complex lipids, polar metabolites, and proteins were simultaneously extracted via a single-step liquid–liquid (MeOH/MTBE/H2O) extraction method, and the corresponding omics datasets were acquired using ultra-high-performance liquid chromatography coupled with high-resolution tandem mass spectrometry and processed with LipidSearch, Progenesis QI, and Proteome Discoverer, respectively. Primarily, we identified characteristic changes in the composition of several lipid species/classes, polar metabolites, metabolic pathways, and protein profiles of serum, liver, and heart tissue homogenates of Pex11α KO mice in comparison to the WT controls. Nevertheless, there are certain limitations in the current study that need to be mentioned. First, serial-omics analyses of distinct biological specimens were performed with a small sample size . Although stringent data analysis criteria were employed, a profound statistical evaluation is restricted due to the limited number of biological replicates, thereby, false positives and/or negatives may not be overruled at this stage. Complementary studies with an independent large sample size may be warranted to elucidate the panel of molecular signatures that were presented in this study and to demonstrate their potential as diagnostic biomarkers. Second, due to medium number of protein identifications, the present study did not allow us to integrate multi-layer omics data to fully capture and represent the complete molecular pathway changes occurring due to Pex11α deficiency. Despite these limitations, to the best of our knowledge, this is the first comprehensive serial-omics study to report the molecular alterations occurring in different biological specimens of Pex11α deficient mice. Further studies addressing changes in other biological specimens , the influence of diet  on molecular alterations, and integrated analysis of multi-omics data with large cohort studies need to be investigated in the near future to gain deeper insights of Pex11α molecular functions and to uncover the pathophysiological mechanisms of peroxisomal disorders.In the present study, we utilized high-throughput mass spectrometry-guided sequential omics workflow and performed comprehensive semi-quantitative lipidomic, metabolomic, and proteomic analyses of different biological specimens  from Supplementary file1 (PDF 2072 kb)Supplementary file2 (PDF 7935 kb)Supplementary file3 (XLSX 1081 kb)Supplementary file4 (XLSX 110 kb)Supplementary file5 (XLSX 400 kb)Supplementary file6 (PDF 637 kb)Supplementary file7 (PDF 605 kb)Below is the link to the electronic supplementary material.


Altogether, 197 chemical compounds were identified or tentatively characterized in the water extraction of XLCQ, 22 of them were selected as the key active constituents that may improve the pathological state by regulating 27 corresponding targets that are mainly involved in inflammation/immune-related pathways, and furthermore, luteolin, apigenin, and chrysoeriol exhibited good anti-neuroinflammatory effects from both protein and mRNA levels. In summary, it is the first time to employ an integrative pharmacology strategy to delineate 22 constituents that may improve the pathological state of stroke with TRFS by regulating 27 corresponding targets, which may offer a highly efficient way to mine the scientific connotation of traditional Chinese medicine prescriptions. This study might be a supplement for the deficiency of the basic research of XLCQ.Xinglou Chengqi (XLCQ) decoction, composed of three botanical drugs and one inorganic drug, is used in clinics during the treatment of acute stroke complicated with Tanre Fushi (TRFS) syndrome in China. However, its active ingredients and the molecular mechanism have not been clarified. So, we aimed to preliminarily characterize its chemical constituents and investigate its pharmacological mechanisms using an integrative pharmacology strategy, including component analysis, network prediction, and experimental verification. We employed UPLC-QTOF-MS/MS to describe the chemical profile of XLCQ, Integrative Pharmacology-based Network Computational Research Platform of Traditional Chinese Medicine (TCMIP v2.0,  Stroke, characterized by a high incidence rate, high mortality, and a high disability rate, is a devastating cerebrovascular event that occurs as a result of cerebral vascular occlusion (ischemic stroke) or burst/bleeding (hemorrhagic stroke), leading to cerebral blood flow disruption, physical disability, and multiple functional impairment, which seriously threatens human health and quality of life . At presTrichosanthes kirilowii Maxim.  30–40 g, Arisaema erubescens  Schott  6–10 g, Rheum palmatum L.  10–15 g, and Natrii sulfas  10–15 g. The main component of Natrii sulfas is Na2SO4•10H2O, which belongs to a mineral medicine.Traditional Chinese medicine (TCM), characterized by lower side effects, is often thought to be an alternative pharmacotherapy for prevention and rehabilitation intervention of ischemic stroke in China . As earlAccumulating clinical practices have proven that the effective power of the Western medicine treatment for acute stroke could be enhanced obviously when combined with XLCQ, especially when the patient is suffering with TRFS . Althoughttp://www.tcmip.cn/), 3) predicting the putative targets of the identified components and collecting the genes of stroke and TRFS from TCMIP, 4) constructing a “component targets-stroke/TRFS genes” network to select the candidate targets and the main active components of XLCQ, 5) functional enrichment analysis for investigating the underlying molecular mechanisms of XLCQ acting on stroke complicated with TRFS, and 6) verifying the anti-neuroinflammatory effects of luteolin, apigenin, and chrysoeriol based on LPS-simulated BV-2 cells.Therefore, in the present study, we aimed to describe the chemical profiles and explore the underlying pharmacological mechanisms of XLCQ acting on stroke with TRFS through the following scheme, as shown in Trichosanthes kirilowii Maxim. , Arisaema erubescens  Schott , Rheum palmatum L. , and Natrii Sulfas  were purchased from Shengshi Baicao Pharmaceutical Co., Ltd. and authenticated by Mrs. Xirong He, a research assistant of China Academy of Chinese Medical Sciences (Beijing). The voucher specimens were deposited in the Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences.HPLC-grade acetonitrile and methanol were purchased from Merck KGaA ; HPLC-grade formic acid from Sigma-Aldrich ; chloroform (100068), isopropanol (80109218), and anhydrous alcohol (10009218) from Sinopharm ; and DEPC-treated water (sc-204391) from Santa Cruz Biotechnology . Deionized water (18.2 MΩ cm) was purified by a Milli-Q system . Fetal bovine serum , penicillin–streptomycin , and 0.05% trypsin-EDTA  from Gibco BRL Co. ; Dulbecco’s Modified Eagle’s Medium-high glucose  from HyClone Laboratories ; dry powder of phosphate-buffered saline , dimethyl sulfoxide , and sterile deionized water (F0025) from Solarbio Life Sciences ; lipopolysaccharide  from Sigma-Aldrich Crop. .Luteolin (BT1191), apigenin (BT443), and chrysoeriol (BT2582) were borrowed from Beijing Beite Renkang Biomedical Technology Co., Ltd. ; IL-1β (CSB-E08054m) and TNF-α (CSB-E04741) ELISA kits from Cusabio ; CCK-8 kit from Dojindo ; and TB Green® Premix Ex Taq™ (RR420A) from TAKARA BIO INC. .The prescription is composed of GL, DNX, DH, and MX with a dose proportion of 15:3:5:5. GL and DNX were soaked in 10 volumes of water for 60 min before boiling for 30 min. Then DH was added and boiling was maintained for another 30 min. MX was dissolved in the decoction that was filtered by eight layers of gauze. The residue was boiled with 8 volumes of water for another 30 min, and the decoction was filtered as before. The two combined filtrates were freeze-dried  at −80°C with a paste rate at 26.96%, and the powder was pressed through a 60-mesh sieve. The fine powder was dissolved into 10 volumes of 70% MeOH and extracted with an ultrasonic wave for 15 min before 1-μl aliquots were transferred to autosampler vials for analysis.The analysis was performed on a Waters Acquity UPLC I-Class system  equipped with a binary pump, an online vacuum degasser, an autosampler, and an automatic thermostatic column oven, coupled with a Waters Xevo G2-S Q-TOF Mass System  equipped with electrospray ionization (ESI). The data were recorded by Masslynx V4.1 . Unifi software  was used for peak detection and compound preliminary identification.Chromatographic separation was performed on a Waters Acquity UPLC HSS T3 column  maintained at 35 °C, and a linear gradient of (A) 0.1% (v/v) formic acid in deionized water and (B) acetonitrile containing 0.1% (v/v) formic acid was used for the elution procedure, as follows: 0–3 min, 0.2–2% B; 3–5 min, 2–5% B; 5–6 min, 5–8% B; 6–10 min, 8–16% B; 10–10.2 min, 16–19% B; 10.2–14.5 min, 19–25% B; 14.5–15 min, 25–30% B; 15–15.5 min, 30–40% B; 15.5–18 min, 40–50% B; 18–20 min, 50–70% B; 20–21 min, 70–98% B; 21–24 min, 98% B; 24–24.1 min, 98–0.2% B; and 24.1–26 min, 0.2% B. The flow rate was set at 0.5 ml/min, and a 1-μl aliquot was set as the injection volume.− capillary voltage, 2.5 KV; and ESI+ capillary voltage, 0.5 KV. At low CE scan, the auto MS collision energy was 6 eV. At high CE scan, the collision energy was 30–50 eV ramp for ESI+ and 80–100 eV ramp for ESI−.The QTOF-MS data were collected in a full scan auto mode from 0 to 26 min in both positive and negative ion modes. Based on the best response for most of the compounds, the optimal parameters were set as follows: mass range, 50–1,500 Da; source temperature, 100 °C; desolvation temperature, 450°C; desolvation gas flow, 900 l/h; sampling cone, 40 V; ESI2O (0.1% formic acid)  for the positive ion mode ([M + H]+ = 556.2771) and negative ion mode ([M−H]− = 554.2615) via a lock spray interface.Leucine enkephalin was employed as lock mass at a concentration of 200 pg/ml in acetonitrile (0.1% formic acid): HE data collected in a continuum mode were processed using the apex peak detection and alignment algorithms in UNIFI 1.8, which enabled quasi-molecular ion peaks, salt adduct ions, and dehydration fragment ions to be analyzed as a single entity. The analysis process includes data acquisition, data mining, library searching, and report generation.UPLC-QTOF-MS/MS system was controlled by the Masslynx 4.1 platform. The MShttp://www.nrc.ac.cn:9090/ETCM/), as a customized library listed in +, [M + K]+, [M + Na]+, [2M + H]+, and [M-e]+ were selected in a positive ion mode and [M + COOH]-, [M-H]-, and [2M-H]- in a negative ion mode. A margin of error up to 5 mDa/10 ppm for identified components was allowed, and the matched components would be generated as predicted fragments from the structure. For unmatched components, the functional module of elemental composition and mass fragment could further assist the chemical identification. Based on the isotopic abundance, the elemental composition calculator could provide a number of possible formulas for an accurate mass peak. Mass fragment could provide fragment structures which assist the chemical identification. The final list of possible formulas could provide relative confidence denoted by an i-FIT score and 0.8 as the threshold value.The information of chemical components GL, DNX, and DH including molecular name, molecular formulas, molecular weights, and chemical structures (mol. format) was collected from ETCM   according to the chemical structure similarity comparison with known drugs on the market. In order to improve the prediction accuracy, we set the structural similarity score at 0.80 (moderate∼high similarity) to select the constitute–putative target pairs .To investigate the relationship of XLCQ putative targets and stroke/TRFS genes, we collected a list of stroke-related genes and TRFS-related genes from disease-related gene database of TCMIP. The key words of stroke were “stroke, ischemic stroke, brain injury, cerebral ischemia, and cerebral hemorrhage.” TRFS syndrome was a combination of Yang Ming Fushi syndrome, phlegm heat obstructing lung syndrome, and wind-phlegm syndrome. So, the symptomatic phenotypes of three syndromes were used as the key words to collect the related genes, including “fever, delirium, abdominal pain, dysphoric mood, hyperhidrosis, constipation, wheezing, cough, vertigo, vomiting, abnormality of salivation, syncope, facial paralysis, and hemiplegia.”An interaction network of XLCQ putative target–stroke/TRFS-related gene was constructed based on the links among the three gene sets using the TCM Association Network Mining Module (TCMNM) of TCMIP, which directly exhibits the major hub network according to three topological features of each node gene, including “degree,” “betweenness,” and “closeness.” Generally, the node that has the degree value 2-fold the median, and betweenness and closeness value 1-fold the median is selected as the major hub.http://bioinformatics.psb.ugent.be/webtools/Venn/). To better exhibit the interactions of the major hubs, the network visualization was performed using CytoScape V3.8.0. To elucidate the biological functions of XLCQ putative targets, the functional enrichment analysis was performed using the database for annotation, visualization, and integrated discovery (DAVID) v6.8 (https://david.ncifcrf.gov).To better exhibit the common targets among XLCQ, stroke, and TRFS, the Venn diagram was performed using the “Calculate and draw custom Venn diagrams” website .Murine BV-2 microglia cells were obtained from the Institute of Materia Medica-Chinese Academy of Medical Science  and cultured in DMEM supplemented with 10% heat-inactivated FBS and antibiotics (100 U/ml streptomycin and 100 U/ml penicillin) at 37°C in an incubator  with a humidified atmosphere containing 5% CO5 cells/well and incubated for 24 h. Luteolin, apigenin, and chrysoeriol solutions were added with final concentrations at 10 μM and incubated for 1 h. Then LPS was added to induce neuroinflammation with a final concentration of 1 μg/ml, and incubated for another 24 h. Finally, the supernatant was collected by centrifugation at 12,000 r and 4 °C for 10 min, which was used for IL-1β and TNF-α analyses according to the instructions of ELISA kits.BV-2 cells were plated in 24-well plates with the density at 1.5 × 10The total RNA was isolated using TRNzol Universal Reagent , and 1 μg RNA was reverse-transcribed to cDNA using FastKing gDNA Dispelling RT SuperMix  by Veriti 96-Well Thermal Cycler PCR  according to the manufacturer’s instructions. A single-stranded cDNA was amplified by PCR with primers for IL-1β, TNF-α, PIK3CA, AKT1, NFKB1, NFKB2, CREB1, HSP0AA1, and β-actin, whose primer sequences are shown in E raw data obtained by UPLC-QTOF-MS/MS were processed using the UNIFI 1.8 software automatically to quickly identify the constituents by matching the detailed information with the customized library (+ and 116 in ESI−) were identified or tentatively characterized, of which 56 originated from GL, 63 from DNX, and 78 from DH. The detailed information of chemical compounds is listed in - = 407.1334 was primarily identified as torachrysone-8-O-β-D-glucoside (C20H24O9) in ESI− after searching in the scientific database of UNIFI collected from ETCM, and the main fragments were m/z 245.0600 [M-H-Glc]-, 230.0560 [M-H-Glc-CH3]-, 215.0324 [M-H-Glc-2CH3]−, 159.0431 [M-H-Glc-2CH3-2CO]−, and 141.0483 [M-H-Glc-2CH3-3CO]− (+ = 268.1046 was primarily identified as arginine (C10H13N5O4) in ESI+, and the main fragments were m/z 136.0624 and 119.0349  chromatograms of water extraction of XLCQ corresponding to the positive and negative ion modes are shown in  library . AltogetH3-3CO]− , which wH3-3CO]− . In the 119.0349 , correspe report .Altogether, a total of 833 putative targets were predicated based on the chemical structures of 197 primarily identified compounds using the TCM Target Prediction and Function Analysis Module of TCMIP . Only 17A total of 159 stroke-related genes and 709 TRFS-related genes were collected from the disease-related gene database of TCMIP . The disTo illustrate the underlying mechanisms of XLCQ acting on stroke complicated with TRFS, an interaction network of drug target genes and disease/syndrome-related genes was constructed based on the interactions among three gene sets using the TCM Association Network Mining Module of TCMIP, and the network topological features were calculated automatically by TCMIP. Altogether, 257 hubs were selected, and detailed information is provided in To improve the prediction accuracy, 150 major hubs whose degree value ≥12 were selected from the 257 hubs .The functional enrichment analysis of the 150 genes was investigated by DAVID v6.8. Altogether, 85 pathways were obtained based on the Reactome Pathway Database. Among them, 52 pathways .There were 60 chemical components corresponding to 150 major hubs. According to the number of major hubs and its frequency appearing in different pathways, the threshold was set at 2 and 13. That was, if a chemical constituent had more than two hubs and simultaneously the frequency of these hubs was more than 13, this chemical constituent was regarded as a key active constituent of XLCQ acting on stroke complicated with TRFS. Altogether, a total of 22 key active constituents and 28 corresponding targets were selected . Twenty-p < 0.0001) and TNF-α (p < 0.05) were significantly increased after BV-2 cells were stimulated by LPS (1 μg/ml) for 24 h, and reversed by pretreatment with luteolin, apigenin, and chrysoeriol at 10 μM for 1 h, suggesting these three compounds had anti-neuroinflammatory activities  using TCMIP, and 159 stroke-related genes and 709 TRFS-related genes were collected from TCMIP. Twenty-two key active constituents were selected based on the interactions among the three abovementioned gene sets, which may improve the pathological state of stroke patients with TRFS syndrome by regulating the 27 corresponding targets that mainly involved in inflammation–immune-related pathways. Luteolin, apigenin, and chrysoeriol, as the predicted components, exhibited good anti-neuroinflammatory effects based on LPS-stimulated BV-2 cells.In the present study, 197 chemical compounds were identified or tentatively characterized in the water extraction of XLCQ analyzed by UPLC-QTOF-MS/MS, and 176 of them had putative targets (Tanimoto score ≥0.8). “Integrative pharmacology” is an interdisciplinary science that comprehensively explores the interactions between the multiple constituents of TCM and the body at multiple levels . TCMIP, 2+ influx and regulate the gene expression in the Ca2+-CaMKII-CREB signaling pathway against cerebral ischemia  synthesis, recycling, salvage and regulation, and VEGFA-VEGFR2 pathway, which associated with apoptosis, inflammation, and nerves, and basically covers all mechanisms of stroke/TRFS, suggesting PI3K/Akt signaling pathways may play an important role in stroke formation (etc. (AKT1 and ormation . PIK3CA on (etc. . GSK3B won (etc. . ADORA3,on (etc. . CASP3 aon (etc. .etc. (According to the prediction results, the rest 9 of the 22 constituents may be involved in anti-inflammatory, regulating energy metabolism, and antiapoptotic by regulating NFKB1, NFKB2, ATP5C1, ATP5A1, AKT1, HSP90AA1, etc. . We seleetc.  to perfoetc. . Chrysoeetc. , arthritetc. , and macetc. , except etc. . Excessietc. . In our In the present study, we just did some basic research about XLCQ, but the particular interactions between the active constituents and the corresponding targets, and if the 22 compounds could represent the whole prescription, still need to be verified in the near future.It is the first time to systematically analyze the chemical composition of XLCQ and to explore the pharmacological mechanisms of XLCQ acting on stroke complicated with TRFS using an integrative pharmacology strategy. The twenty-two key active constituents may improve the pathological state by regulating 27 corresponding targets that are mainly involved in inflammation–immune-related pathways. The integrative pharmacology strategy may offer a highly efficient way to mine the scientific connotation of traditional Chinese medicine prescriptions. This study might be a supplement for the deficiency of the basic research of XLCQ.


We documented that although the global abundance and distribution of m6A remained unchanged, a greater number of genes had gained an m6A modification in the hybrid. Superior variations were observed at the m6A modification and translational efficiency levels when compared with mRNA abundance between the hybrid and parents. In the hybrid, the vast majority of genes with m6A modification exhibited a non-additive expression pattern, the percentage of which was much higher than that at levels of mRNA abundance and translational efficiency. Non-additive genes involved in different biological processes were hierarchically coordinated by discrete combinations of three regulatory layers. These findings suggest that transcriptional and post-transcriptional regulation of gene expression make distinct contributions to heterosis in hybrid maize. Overall, this integrated multi-omics analysis provides a valuable portfolio for interpreting transcriptional and post-transcriptional regulation of gene expression in hybrid maize, and paves the way for exploring molecular mechanisms underlying hybrid vigor.Heterosis has been extensively utilized to increase productivity in crops, yet the underlying molecular mechanisms remain largely elusive. Here, we generated transcriptome-wide profiles of mRNA abundance, m 1 hybrid and its parental lines showed dissimilarities of regulatory and heterotic patterns of genes undergoing hierarchical regulation at the mRNA abundance, m6A modification, and translational efficiency.A maize F In plants, heterotic traits are mainly related to growth rate, biomass, stress tolerance, and seed yield. All these traits are crucial for increasing crop yield. The widespread application of heterosis is one of the landmark innovations of modern agriculture, and breeding hybrids has proved to be one of the most efficient ways to increase grain yield of various crops  is the most prevalent covalent modification in mRNA and long non-coding RNA , and how they may regulate RNA metabolism  in a growth chamber (16 h of light at 28 °C and 8 h dark at 25 °C). Positioning of the F1 hybrid and parental plants was randomized every day. After 14 d, aerial tissues were harvested, immediately frozen in liquid nitrogen and stored at −80 °C for subsequent experiments. The other batch of plants (n=15) were used to investigate heterotic traits, including plant height and fresh weight. Statistical significance of differences of heterotic traits was determined using Student’s t-test.The maize F3COONH4 (pH 5.3) at 42 °C for 3 h, followed by the addition of 1 U shrimp alkaline phosphatase (NEB) and 10% (v/v) Cutsmart buffer and incubated at 37 °C for 3 h. Then the sample was diluted to 50 μl and filtered through a 0.22 μm polyvinylidene difluoride filter (Millipore). Finally, 10 μl of the solution was used for LC-MS/MS. Nucleosides were separated using reverse-phase ultra-performance liquid chromatography on a C18 column coupled to online mass spectrometry detection using an Agilent 6410 QQQ triple-quadrupole LC mass spectrometer in positive ion mode. The nucleosides were quantified by comparison with the standard curve obtained from pure nucleoside standards run in the same batch as the samples. The ratio of m6A/A was calculated based on the calibration curves.Two hundred nanograms of mRNA was digested with 1 U Nuclease P1 (Wako) in buffer containing 10% (v/v) 0.1 M CH6A immunoprecipitation was performed using the Magna methylated RNA immunoprecipitation (MeRIP) m6A kit (Millipore) following the manufacturer’s protocol. In brief, 27 μg mRNA was fragmented and ethanol precipitated and 0.5 μg RNA was removed as input control. Meanwhile, 30 μl magnetic A/G beads was incubated with 10 μg anti-m6A antibody (MABE1006) in 1× immunoprecipitation (IP) buffer for 30 min at room temperature. Then all remaining fragmented mRNA was incubated with the antibody–beads at 4 °C for 2 h with rotation. After being washed three times with 1× IP buffer, bound RNA was eluted from the beads with 100 μl elution buffer twice and then purified with the RNA Clean & Concentrator Kit (Zymo). Both purified sample and input control were used for library construction.Total RNA was extracted using TRIzol reagent (Thermo Fisher Scientific) and polyadenylated RNA was subsequently isolated with the GenElute mRNA Miniprep Kit (Sigma-Aldrich) according to the manufacturer’s instructions. m2, 25 mM EGTA, 1% (v/v) Tween 20, 1% (v/v) Triton X-100, 2% (v/v) polyoxyethylene, 5 mM dithiothreitol, 500 μg ml−1 heparin, 100 μg ml−1 chloramphenicol, and 25 μg ml−1 cycloheximide). After centrifuging at 13 200 g for 15 min at 4 °C, the supernatant was loaded on top of a 1.7 M sucrose cushion and centrifuged at 246 078 g (SW55Ti rotor in a Beckman L-100XP ultracentrifuge) for 3 h at 4 °C. The pellet was washed with RNase-free water and resuspended with 200 μl resuspension buffer . Then the solution was loaded onto a 20–60% sucrose gradient and centrifuged at 204 275 g (SW55Ti rotor) for 2 h at 4 °C. The sucrose gradients were monitored and fractionated with a gradient fractionator . The polysomal RNA fractions were collected and extracted for library construction.Polysome profiling was performed as previously described  following the manufacturer’s protocol and sequenced on the Illumina HiSeq X Ten platform using 150 bp paired-end sequencing.Libraries of RNA-seq, m1 hybrid and parents, filtered reads from B73 and F1 hybrid B73×Mo17 were mapped to the maize B73 reference genome (AGPv4.38)    by the software StringTie v1.3.3  at fold-change ≥1.5 and P<0.01. Similarly, differentially translated genes were identified by the Xtail package (v1.1.5)   A≠0, B≠0, A=B). If parents showed significant divergence but not F1 allelic expression, genes were considered to be caused by only trans effects ((ii) A≠0, B=0, A≠B). Genes exhibiting F1 allelic divergence that significantly diverged from parental gene expression divergence ((iii) A≠0, B≠0, A≠B) were considered to be enhancing or compensating, which was dependent on whether the cis and trans effects were in the same or opposite directions, respectively. When F1 allelic expression showed significant divergence but not between parents, genes were considered as fully compensatory ((iv) A=0, B≠0, A≠B). Genes belonging to category (iii) and (iv) were combined and defined as both cis and trans effect. Neither parental gene expression divergence nor F1 allelic expression divergence was detected, which was defined as conserved genes ((v) A=0, B=0, A=B).Unique reads of the Fmer v3.0  was used6A-IP, input, and polysome profiling was used for reverse transcription with the PrimeScriptTM RT reagent Kit with gDNA Eraser (TaKaRa). RT-qPCR was performed with TB Green Premix Ex Taq (TaKaRa) using a Bio-Rad CFX96 real-time PCR detection system. Zm00001d034600 and Zm00001d042939 were used as internal control genes due to their invariant expression among hybrid and two parental lines B73 and Mo17 for all the three levels of mRNA abundance, m6A methylation, and translational efficiency according to the sequencing data. All primers used in this study are listed in RT-qPCR was performed as described in 1 hybrid B73×Mo17 as research targets. Significant growth vigor in the F1 hybrid was observed at the early seedling stage 14 d after sowing (DAS)  and better parent value (BPV), respectively  . We compectively . The freectively . These r6A/A ratio of purified mRNA by using LC-MS/MS to show the global abundance of m6A modification in planta. As shown in 6A/A ratio between the F1 hybrid and the two parental lines, suggesting that the global m6A methylation abundance remains relatively stable in the hybrid.To explore whether epitranscriptomic regulation of gene expression is associated with heterosis, we firstly measured the m6A methylation in gene expression in the hybrid, we generated transcriptome-wide integrated maps of mRNA abundance, m6A methylation, and translational efficiency by conducting input RNA sequencing (RNA-seq), m6A RNA immunoprecipitation sequencing (m6A-seq)  and in the vicinity of the stop codon , but were less present in coding sequences , near start codons , in the 5′UTR (~0.6%), and in the spliced intronic regions  were identified in the hybrid in comparison with the parental line B73 (n=11 185) and Mo17 (n=9480)  and Mo17 (n=7490) lines  , althougal lines . Accordi n=9118;  was grea0) lines . Interese hybrid . These r6A modification, and translational efficiency in the hybrid relative to the parental lines, six pairwise comparisons were performed per regulatory layer. Intriguingly, fairly distinct patterns in the pairwise comparisons between hybrid and parents and between parents were observed among the three regulatory layers. At the mRNA abundance level, the number of differentially expressed genes in parent–hybrid comparisons was substantially less than in parent–parent comparisons, with 4805 genes between parents in comparison with 2109 and 2916 genes in the hybrid relative to B73 and Mo17, respectively <0.01) as non-additive genes at each of the mRNA abundance, m6A modification, and translational efficiency levels. Strikingly, we observed that the percentage and number of non-additive genes were extraordinarily different at each of the three regulatory layers in the hybrid. In particular, 44.3% of m6A-modified genes (n=4826) were non-additive  were moderately lower than those of down-regulated genes , the numbers and proportions of up-regulated genes at both the m6A modification  and translational efficiency level  were much greater than those of down-regulated genes  , high parent , low parent , and below lower parent  . Again, ctively) , suggest6A methylation, and translational efficiency. Interestingly, we found that parental variances in m6A methylation contributed more to heterotic variances relative to mRNA abundance and translational efficiency. In detail, 63.9% of non-additive m6A-modified genes (n=3085) could be explained from parental variances, whereas only 36.2% (n=525) and 3.3% (n=83) could be explained at the mRNA and translational efficiency levels, respectively. Together, these results clearly indicate that transcriptional and post-transcriptional regulation of gene expression participate differently in the formation of heterosis in the maize hybrid.To characterize parent-of-origin effects on gene activity, we compared parental and heterotic variances at the levels of mRNA abundance, med genes , n=3085 ly 36.2% , n=525 aand 3.3% , n=83 co6A in epitranscriptomic regulation of gene expression prompted us to investigate its effects on mRNA abundance and translational efficiency. As shown in 6A level showed a decreased level of mRNA abundance compared with genes in the LP and BLP groups, suggesting that m6A modification may be actively involved in mRNA decay in the hybrid. Likewise, genes in the HP and AHP groups categorized by m6A level exhibited a tendency for decreased level of translational efficiency compared with genes in the LP and BLP groups  and contained the maximum number of genes (n=278) identified in all the clusters. The opposite patterns of transcription and translation indicates that a high level of mRNA of genes involved in response to stimulus pathway may be substantially attenuated by decreased translational activity, and this attenuation is likely not dependent on m6A modification.In cluster 3, which was signified by a high level of mRNA abundance and mitropism . The oppficiency . The enrficiency . Interes6A modification  were observed at the level of m6A modification  terms for all eight clusters identified in erab074_suppl_Supplementary-Figures-S1-S6Click here for additional data file.erab074_suppl_Supplementary-Tables-S1-S6Click here for additional data file.


Haemophilus influenzae strain KW20. Here, we tested the hypothesis that some NfsB homologs function as housekeeping enzymes with the potential to become chloramphenicol resistance enzymes. We found that expression of H. influenzae and Neisseria spp. nfsB genes, but not Pasteurella multocidanfsB, allows Escherichia coli to resist chloramphenicol by nitroreduction. Mass spectrometric analysis confirmed that purified H. influenzae and N. meningitides NfsB enzymes reduce chloramphenicol to amino-chloramphenicol, while kinetics analyses supported the hypothesis that chloramphenicol reduction is a secondary activity. We combined these findings with atomic resolution structures of multiple chloramphenicol-reducing NfsB enzymes to identify potential key substrate-binding pocket residues. Our work expands the chloramphenicol reductase family and provides mechanistic insights into how a housekeeping enzyme might confer antibiotic resistance.Phylogenetically diverse bacteria can carry out chloramphenicol reduction, but only a single enzyme has been described that efficiently catalyzes this reaction, the NfsB nitroreductase from IMPORTANCE The question of how new enzyme activities evolve is of great biological interest and, in the context of antibiotic resistance, of great medical importance. Here, we have tested the hypothesis that new antibiotic resistance mechanisms may evolve from promiscuous housekeeping enzymes that have antibiotic modification side activities. Previous work identified a Haemophilus influenzae nitroreductase housekeeping enzyme that has the ability to give Escherichia coli resistance to the antibiotic chloramphenicol by nitroreduction. Herein, we extend this work to enzymes from other Haemophilus and Neisseria strains to discover that expression of chloramphenicol reductases is sufficient to confer chloramphenicol resistance to Es. coli, confirming that chloramphenicol reductase activity is widespread across this nitroreductase family. By solving the high-resolution crystal structures of active chloramphenicol reductases, we identified residues important for this activity. Our work supports the hypothesis that housekeeping proteins possessing multiple activities can evolve into antibiotic resistance enzymes. Rates of infection by antibiotic-resistant bacteria are steadily increasing. Annual deaths due to previously curable bacterial infections in the United States are estimated between 23,000 and greater than 150,000 and are predicted to reach 10 million globally by the year 2050 13. Among 4–Haemophilus influenzae homolog of the NfsB nitroreductase enzyme can confer clinical levels of antibiotic resistance when expressed in Escherichia coli  has the ability to reduce chloramphenicol to amino-chloramphenicol in vitro , H. influenzae strain 12 (Hi 12), H. influenzae strain 86-028NP (Hi 86-028NP), Neisseria gonorrhoeae strain FA1090 (Ng FA1090), N. meningitidis strain Z2491 (Nm Z2491), and Pasteurella multocida strain 70 (Pm 70). These NfsB homologs included enzymes predicted to reduce  or not reduce (Pm 70) chloramphenicol based on the phenotypes detailed in Smith et al. . The two Neisseria-derived NfsB enzymes show high amino acid identity (96.83%) to each other but only moderate identity to the H. influenzae homologs (56.82% to 59.09%). Finally, the P. multocida NfsB protein shares between 58.64% and 61.19% amino acid sequence identity to the other homologs  despite being evolutionarily more closely related to H. influenzae (shared family Pasteurellaceae) than Neisseria sp. (shared phylum of Proteobacteria).Previous work has demonstrated that the NfsB enzyme from in vitro –17. Smit culture . In ordeEs. coli expressing each nfsB homolog identified above for reduction of the chloramphenicol nitro group to an amine. Dense cultures of each Es. colinfsB-expressing strain were washed and incubated with chloramphenicol to initiate reduction of the nitro group . Pr. PrEs. cro group , 15, 20 t signal , with thEs. coli and Es. coli expressing a chloramphenicol acetyltransferase (cat) gene or the Hi KW20 nfsB gene by cultivation at inhibitory concentrations of amphenicol antibiotics. These antibiotics included chloramphenicol (vulnerable to both resistance mechanisms), thiamphenicol , florfenicol , and the amphenicol analog Sch-24893   . Expressfficient .nfsB-expressing Es. coli strain compared to a vector control. Concentration-response curves of overnight growth measured against various concentrations of chloramphenicol were generated  and used to calculate the chloramphenicol 50% inhibitory concentration (IC50) for each strain. Expression of any of the H. influenzae or Neisseria nfsB homologs was sufficient to significantly increase the resistance of Es. coli to chloramphenicol (q < 0.05 to q < 0.0005), while expression of the P. multocidanfsB resulted in a negligible but significant increase in susceptibility instead (q < 0.0005) (H. influenzae or Neisseria nfsB expression ranged from approximately a 16-fold increase (Hi KW20 and Hi 86-028NP) down to an ∼2-fold increase (Hi Int1 and Hi 12). The chloramphenicol MICs for each strain followed this same pattern .Finally, we measured the chloramphenicol susceptibility of each  0.0005) . The relin vitro study. Each nfsB homolog was cloned into a new inducible plasmid for overexpression in Es. coli. Each histidine-tagged construct was purified by affinity chromatography followed by enzymatic removal of histidine tags. All four H. influenzae NfsB enzymes and Nm Z2491 NfsB expressed well as soluble proteins, while the Ng FA1090 and Pm 70 enzymes resulted in production of insoluble protein.We next overexpressed and purified NfsB enzymes for H. influenzae and N. meningitidis NfsB enzymes reduce chloramphenicol to amino-chloramphenicol. The absence of standards for unstable reduction intermediates, such as nitroso- and hydroxylamino-chloramphenicol, prevented the targeted detection of these compounds. We set up minimal enzymatic reactions  with excess equivalents of NADPH (previously shown to be the preferred electron donor of Hi KW20 NfsB [We used liquid chromatography mass spectrometry (LCMS) to determine if the W20 NfsB ) and ana+ of m/z 323.0198 and an [M + Na]+ of m/z 315.0274, respectively . This contrasts with our Es. coli-based assays (q < 0.005) than Hi KW20 NfsB as measured by catalytic efficiency (kcat/mK). The Hi Int1 and Hi 86-028NP enzymes showed comparable, although statistically significant, kinetics (q < 0.05) to Hi KW20 NfsB. In contrast, Nm Z2491 NfsB was much less active in vitro, with ∼15% the activity as Hi KW20 NfsB (q < 0.0005), apparently driven by a much larger mK value   . As expeficantly .in vitro. The 1.15-Å structure (2 solvent-excluded surface), which also includes the binding pocket for a substrate  of the isoalloxazine ring. It makes hydrogen bonds with O2′ of the FMN ribityl tail (2.7 Å) and N (2.8 Å) of V47 from the second monomer  and NH2 (3.1 Å) of R16 and with OG of S18 (2.7 Å); O3P with N of S18 (2.8 Å) and with OG of S17 (3.2 Å); and O1P with NH2 of R16 (3.2 Å), with NZ of K207 (2.8 Å), and with NH2 of R209 (2.7 Å). There are additional van der Waals contacts through P165 and from the second protomer with P44. The acetate molecule, a small substrate analog, is on the “ monomer . The proTo understand better how variation in the substrate-binding site mediates activity, we solved the crystal structures of the NfsB homologs from Hi KW20, Hi Int1, Hi 86-028NP, and Nm Z2491 . We alsoH. influenzae proteins and 0.9 Å for the Nm Z2491 structure. To test the hypothesis that the observed catalytic differences  (PDB: 5J8D) or 4-nitrobenzoic acid (comparable to chloramphenicol and 4-nitrophenol) (PDB: 5J8G) (En. cloacae structure [5J8D]). Similarly, when Hi 12 NfsB contains 4-nitrophenol in its active site, Trp71 swings out, with movement potentially of the whole α3-to-α4 loop, to avoid a clash with the 4-nitrophenol NO2 group. This movement appears to be supported through an interaction with the Met74 side chain  of Cα atoms among these structures are very small with a range of 0.36 to 0.61 Å for the ferences  arise frB: 5J8G) . The maiB: 5J8G) . These rde chain , in whicde chain .En. cloacae structures complexed with 4-nitrobenzoic acid or NAAD , as opposed to coenzyme binding , we focused on comparisons between the Hi 12 NfsB structure complexed with 4-nitrophenol, the Nm Z2491 structure complexed with nicotinic acid, and the previously published  or NAAD . The phe defined . These t defined . This sunfsB housekeeping gene from H. influenzae KW20 (Hi KW20) is sufficient to confer clinically relevant levels of chloramphenicol resistance in Es. coli  and similar in vitro chloramphenicol reduction kinetics (Es. coli (H. influenzae 12 NfsB retains greater than 94.98% identity with the other H. influenzae NfsB homologs (Table S1), it showed a significantly greater catalytic efficiency in vitro  spectrum revealed pure amino-chloramphenicol (data not shown). We are therefore confident that abiotic gas-phase dehydration reactions during LCMS analysis are responsible for the formation of the amino-chloramphenicol-related metabolites and not additional enzymes in an uncharacterized pathway or nonenzymatic processes as originally hypothesized , they are in line with other reported canonical antibiotic-modifying enzymes, including aminoglycoside acetyltransferases and phosphotransferases   locus. This suggests that in some contexts, nfsB homologs play a role in bacterial responses to antibiotics, pollutants, and other xenobiotics (The apparently moderate in vitro . When exred here  are loweM−1 s−1) , 28, sugobiotics .Previous kinetic studies of nitroreductase catalysis revealed that reactions progress by a double-displacement (ping-pong) mechanism that appears to lack the gating steps necessary to impose specificity, explaining the substrate promiscuity of these enzymes. In this mechanism, two electrons are transferred as a hydride from NAD(P)H to the oxidized FMN and from reduced anionic FMN to substrate  21). Hy. Hy21). H. influenzae NfsB homologs at only eight amino acid positions . Among these, residues S68 and M74 appear to be particularly well positioned to influence substrate binding (H. influenzae strains (Table S1), the in vitro activity differences of these proteins . A glycine residue at the equivalent position in En. cloacae NfsB has similarly been hypothesized to provide greater loop flexibility    suggest H. influenzae strain KW20 NfsB but is distributed across multiple taxa  , sodium nitrite , ammonium sulfamate , riboflavin 5′-monophosphate sodium salt (FMN) , and florfenicol (NC1617017) were purchased from Fisher Scientific and prepared as described below. β-Nicotinamide reduced tetrasodium salt (NADPH) was purchased from Dot Scientific , stored dry at −20°C, and prepared fresh for all experiments. Amino-chloramphenicol was purchased from Toronto Research Chemicals (A622670) as an HCl salt and prepared by dissolution in water. Amino-chloramphenicol solutions were stored at −20°C for less than 1 month. Sch-24893 , thiamphenicol , and kanamycin sulfate (KAN) (K1377) were purchased from Sigma-Aldrich and prepared as 50 mg/mL stock solutions in ethanol (amphenicols) or water, filter sterilized, and stored at −20°C. Bratton-Marshall reagent  . When necessary for plasmid maintenance, the antibiotic kanamycin (KAN) was included at 50 µg/mL final concentration .Routine cultivation of H. influenzae Rd KW20 (Hi KW20) NfsB enzyme were identified in the genomes of H. influenzae strains Hi Int1, Hi 12, and Hi 86-028NP and from the genomes of Neisseria gonorrhoeae FA1090, Neisseria meningitidis Z2491, and Pasteurella multocida Pm70 by reciprocal protein BLAST search H-flavin oxidoreductases with corresponding GenInfo Identifier (gi) number were targeted for study: H. influenzae Rd KW20 , H. influenzae R2846 , H. influenzae R2866 , H. influenzae 86-028NP , N. meningitidis Z2491 , Pasteurella multocida Pm70 , and N. gonorrhoeae FA1090 . Each ORF was amplified by PCR by Q5 high fidelity polymerase  according to manufacturer recommendations with primers that contained 25-bp homology to pZE21-derived expression vector at the 5′ ends (Table S2)  (Table S2) and agarose gel electrophoresis were used to verify the presence of inserts, and sequence integrity was confirmed by Sanger sequencing .Open reading frames (ORFs) of the genes selected for study were codon optimized for expression in able S2) , 37. Q5 Es. coli cells expressing nfsB homologs was determined by a modification of the Merkel and Steers method , and cultures were found to be uniform. Cultures were transferred onto ice and centrifuged at 4,000 relative centrifugal force (rcf) for 2 min to pellet cells. After supernatants were decanted, the cell pellets were resuspended on ice in 400 µL of 4°C MDG minimal medium , 0.4% glucose, 2 mM MgSO4, 0.2× trace metals solution , and 50 µg/L leucine. To quench the t zero time point, cells were pelleted again as described above, and 100 µL of supernatant was removed from each sample directly into 100 µL of 20% trichloroacetic acid in water and held on ice. The cell pellets were resuspended into the remaining supernatant volume and incubated at 37°C. Additional quenches were performed as described above at 2.5 h and 5 h. After the final quench, each supernatant sample in 10% trichloroacetic acid was derivatized by the Bratton-Marshall method to detect aromatic amines (N-(1-naphthyl)ethylenediamine dihydrochloride , with a 10-min room temperature incubation between each step. The relative quantity of aromatic amine was determined by measurement of the absorbance of each reaction at 550 nm on an Epoch Microplate Spectrophotometer (Biotek Instruments). The time series data were used to determine the apparent rate of chloramphenicol reduction in quadruplicate for each strain. Rates for each nfsB-expressing strain were compared to the empty vector control strain and tested for significance using Brown-Forsythe and Welch analysis of variance (ANOVA) tests with false-discovery rate correction by the method of Benjamini, Krieger, and Yekutieli, as implemented in GraphPad Prism 8.0 .Chloramphenicol reduction by resting s method . Four col medium  supplemec amines , 20 by tn = 4 biological replicates) of Es. coli strains containing an empty pZE21 vector, pZE21 expressing chloramphenicol acetyltransferase (cat), or pZE21 expressing the Hi KW20 nfsB gene were inoculated into 1 mL of MH + KAN50 broth and incubated overnight at 37°C with shaking. Following growth, each culture was normalized to an OD600 of ∼1 absorbance unit (AU) by dilution in fresh MH + KAN50 broth and inoculated to an initial OD600 of 0.025 into 200 µL of MH + KAN50 broth supplemented with chloramphenicol, thiamphenicol, florfenicol, or Sch-24893 at 4 µg/mL in a 96-well flat-bottomed plate. The plate was sealed with a Breath-Easy membrane  to prevent evaporation  were taken on uninoculated wells with MH + KAN50 broth. Strain growth was determined by taking the average of four replicate results for each strain-amphenicol combination and evaluated using an ordinary two-way ANOVA with multiple comparison correction using the procedure of Benjamini, Krieger, and Yekutieli, as implemented in GraphPad Prism 8.0.Four colonies each  for a total of n = 8 biological replicates. For each replicate, a single colony grown on LB + KAN50 agar was picked into MH + KAN50 liquid medium and incubated aerobically overnight at 37°C. The optical density of each culture was measured at 600 nm, and cultures were adjusted by addition of MH + KAN50 to give an initial density of between 0.75 and 1.25 absorbance units. These were used to inoculate MH + KAN50 cultures in a 96-well flat-bottomed plate with final volumes of 205 µL, each across a 12-step 2-fold dilution series of chloramphenicol ranging from 256 µg/mL to 0.125 µg/mL at an initial OD600 of between 0.02 and 0.05 absorbance units. The 96-well plates were sealed with a Breath-Easy membrane and incubated with shaking at 37°C for 20 h to 24 h. To read culture densities, the sealing membrane was removed to allow for manual resuspension of cell clumps prior to absorbance measurement at 600 nm on an Epoch microplate reader. Blank readings and pathlength correction (1 cm) were taken on control wells and applied to each plate prior to plotting final optical density against chloramphenicol concentration. The 50% inhibitory concentration (IC50) for each individual replicate was calculated by plotting the 4-factor sigmoidal function with a baseline of 0 using GraphPad Prism 8.0. Results for Es. coli expressing wild-type nfsB genes were evaluated for significance by comparison to empty vector controls using a Brown-Forsythe and Welch ANOVA test with Benjamini, Krieger, and Yekutieli false-discovery correction for multiple comparison in GraphPad Prism 8.0.The chloramphenicol susceptibility assays below were performed twice in quadruplicate for each H. influenzae Rd KW20 , H. influenzae R2846 , H. influenzae R2866 , H. influenzae 86-028NP , N. meningitidis Z2491 , Pasteurella multocida Pm70 , and N. gonorrhoeae FA1090  were amplified from genomic DNA by KOD Hot Start DNA polymerase , treated with T4 polymerase in the presence of dCTP, and cloned into the pMCSG53 vector and overexpressed in Es. coli BL21(DE3)-Gold (6 tag with a tobacco etch virus (TEV) nuclear-inclusion-a endopeptidase (EC 3.4.22.44) protease cleavage site fused with the target protein. To test enzyme stability and solubility, a single colony for each homolog was picked into LB and induced with isopropyl-β-d-thiogalactoside (IPTG) overnight at 18°C. The cell lysates were analyzed for the presence of expressed proteins with the correct molecular weights and for protein solubility by small-scale nickel-nitrilotriacetic acid (Ni-NTA) affinity purification and TEV protease cleavage . The P. multocida and N. gonorrhoeae enzymes were found to be insoluble, and their large-scale expression was not pursued.Highly purified NfsB enzymes were prepared following the protocols established under the Midwest Center for Structural Genomics (MCSG) and the Center for Structural Genomics of Infectious Disease (CSGID) . NAD(P)HE3)-Gold . The pMC600 of ∼0.9 followed by incubation for 60 min at 4°C. Per liter of culture, 20 mL of l-SeMet with inhibitory amino acids (IAAC) solution was added followed by 0.5 mM IPTG after 20 min. After induction, all cell cultures were incubated overnight at 180 rpm at 18°C. The harvested cells were spun down at 7,000 rcf  and resuspended in 25 mL of lysis buffer  with protease inhibitor cocktail . Lysozyme (Sigma) was added at a concentration of 1 mg/mL just before cells were stored at −80°C.For large-scale expression, cells were grown in 2-L plastic bottles in enriched M9 medium for selenomethionine (SeMet)-labeled proteins . Cell cu+2 using an AKTA Express System (Cytiva). Since the recombinant TEV protease carried a noncleavable His6 tag  for 80 min, followed by filtration through a 0.45-µm filter (Millipore). Proteins were purified by Ni-immobilized metal affinity chromatography (IMAC-I) using a 5-mL HiTrap Chelating HP column charged with NiHis6 tag , a seconThe purified proteins were buffer exchanged into 20 mM Tris pH 7.5, 40 mM KCl, 0.1 mM FMN, and 1 mM tris(2-carboxyethyl) phosphine  buffer and concentrated using an Amicon Ultra-15 centrifugal filter device (Millipore). The final concentrations were 67.9 mg/mL for Hi KW20, 123.6 mg/mL for Hi 12, 72.3 mg/mL for Hi Int1, 67.1 mg mL for Hi 86-028NP, and 51.1 mg/mL for Nm Z2491.in vitro characterization, all soluble protein stocks  were diluted 100-fold in 50 mM Tris pH 8 buffer and requantified by bicinchoninic acid (BCA) assay  against a bovine serum albumin standard. Enzyme aliquots were normalized to an initial concentration of 0.2 µM based on the BCA assay values. To standardize reaction conditions, reduction of chloramphenicol to amino-chloramphenicol using NADPH was monitored by Bratton-Marshall assay. Soluble enzymes at 0.2 µM were each added to eight wells of a 96-well plate in 50-µL aliquots. To each well was added 50 µL of 500 µM (each) chloramphenicol and NADPH in 50 mM Tris. One reaction well for each enzyme was quenched with trichloroacetic acid approximately every minute for 7 min and analyzed by Bratton-Marshall derivatization as described above to generate a reaction product curve for the formation of amino-chloramphenicol.Prior to in vitro reaction was set up for each enzyme consisting of 4 mM NADPH, 1 mM chloramphenicol, and 1 μM enzyme in a 300-μL final volume. The usual components of buffer and saturating FMN were omitted to avoid potential matrix effects during LCMS analysis. Reactions were initiated by addition of enzyme and were incubated at room temperature (∼23°C) for 1 h before they were quenched by addition of 250 μL of ice-cold acetonitrile. Additional reactions with variable NADPH concentrations using only the Hi 12 NfsB enzyme were prepared as described above with NADPH at 0 mM, 1 mM, 2 mM, or 3 mM and allowed to incubate for 20 min before they were quenched. Two control reactions were performed as follows: one reaction with only enzyme omitted, and one reaction with enzyme omitted and with amino-chloramphenicol spiked in at a final concentration of 1 mM.To characterize the final product of chloramphenicol reduction, a simplified −1 on a Phenomenex Kinetex C18 RP-HPLC column  fitted with a Phenomenex SecurityGuard Ultra UHPLC guard cartridge. The 5-min UHPLC method consisted of an isocratic flow of 100% water for 0.25 min, a gradient of 0% to 45% aqueous acetonitrile for 3.95 min, a gradient of 45% to 100% aqueous acetonitrile for 0.20 min, and an isocratic flow of 100% acetonitrile for 0.1 min. Mass spectral data were acquired using a 200 to 900 m/z scan range at a resolution of 35,000, a maximum inject time of 200 ms, and an automatic gain control (AGC) target value of 1 × 106. Tandem MS data were collected at a resolution of 17,500, a maximum inject time of 250 ms, an AGC target value of 5 × 106, and stepped higher-energy collisional dissociation (HCD) energies of 20, 30, and 40 eV. The heated electrospray ionization source (HESI) was optimized to a spray voltage of 3.5 kV, a vaporizer temperature of 250°C, sheath gas pressure of 60 lb/in2, and auxiliary gas pressure of 15 lb/in2 to mitigate chloramphenicol in-source gas-phase reactions. Parallel reaction monitoring with a 2.0 m/z isolation window and an ion m/z inclusion list ensured that chloramphenicol-related ions were targeted for fragmentation. Data were analyzed using Thermo Xcalibur Qual Browser software version 4.0.27.10.Quenched reactions were filtered through 0.45-μm high-performance liquid chromatography (HPLC) filter vials  and analyzed by LCMS/MS using an Agilent 1290 Infinity II ultra-high-performance liquid chromatograph (UHPLC) coupled with a Q-Exactive mass spectrometer (Thermo Fisher Scientific). Reversed-phase (RP) chromatography was performed with water and acetonitrile as mobile phases at a flow rate of 700 µL minε340 = 6,220 M−1 cm−1 :The Michaelis-Menten kinetics of chloramphenicol reduction by NADPH was performed as previously described . BrieflyM−1 cm−1 . Rates wkcat, mK, and kcat/mK, which are found in Curves fit to all four replicates were plotted, and each replicate was analyzed individually to calculate mean and error statistics for kcat, mK, and kcat/mK as above and are found in Determination of NADPH oxidation kinetics for each enzyme was performed as described above. Reactions were performed in quadruplicate in 100-µL volumes that contained 50 mM Tris buffer pH 8, 1 mM chloramphenicol, 1 µM FMN, and NADPH in concentrations from 500 µM to 31.25 µM and 0 µM. After initiation by addition of enzyme to a final concentration of 0.1 µM, NADPH oxidation was monitored as above. Initial reaction slopes were converted to rates and plotted to determine Crystallization experiments for NfsB SeMet-labeled proteins of Hi KW20, Hi 12, Hi Int1, Hi 86-028NP, and Nm Z2491 were performed by the sitting drop vapor-diffusion method with the help of a Mosquito liquid handler instrument (TTP Labtech) in 96-well CrystalQuick plates . Briefly, 0.4 μL of purified protein was mixed with 0.4 μL of crystallization solution and equilibrated over 135 μL of INDEX (Hampton Research), MCSG1, and MCSG4 (Anatrace), and PEGsII Suit  well screening solutions. The final protein concentrations used in crystallization droplets were 11.3, 20.5, 12.1, 11.2, and 8.5 mg/mL for Hi KW20, Hi 12, Hi Int1, Hi 86-028NP, and Nm Z2491, respectively. The protein-to-ligand ratio in cocrystallization experiments was approximately 1:30. All crystallizations were performed at 16°C. Crystals suitable for structure determination appeared within a day and continued to appear under different crystallization conditions over the course of 3 to 4 weeks. For Hi 12 NfsB in complex with acetate, the best crystals grew under the MCSG1 D10 condition ; for the Hi 12 NfsB and 4-nitrophenol complex, the best condition was MCSG1 E3  550); for Hi KW20 NfsB, the best condition was MCSG 1 C1 ; for Hi Int1 NfsB, the best condition was MCSG1 C5 (0.2 M magnesium acetate and 20% [wt/vol] PEG 3350); for Hi 86-028NP NfsB, the best condition was MCSG1 E9 ; and for Nm Z2491 NfsB in complex with nicotinic acid, the best condition was MCSG1 C7 .Before data collection, crystals in mother liquor plus typically 25% ethylene glycol were flash-frozen in liquid nitrogen. The crystal diffractions were measured using a Pilatus3 X 6M detector (SBC19-ID) or ADSC Q315r detector (SBC 19-BM) at a temperature of 100 K at the Structural Biology Center 19-ID or 19-BM beam line of the Advanced Photon Source . The diffraction data were indexed, integrated, and scaled using HKL3000 suite .1/2 and Ramachandran favored/outlier percentages were determined by standard methods  using shelxc/d/e  to find  methods , 53. ThrRwork and Rfree of 0.142 and 0.159, respectively, with a resolution of 1.15 Å and contains 221 residues, including the N-terminal artifact residues, an FMN molecule, an acetic acid molecule, Ca and Cl ions, a formic acid molecule, and 187 water molecules. The final 1.45-Å structure of the Hi 12 NfsB.4-nitrophenol complex has an Rwork/Rfree of 0.148/0.190 and includes the protein dimer, with chain A consisting of 223 residues (−2 to 220) and chain B consisting of 218 residues (3 to 220) missing five residues (including three purification artifact residues) at the N terminus. In addition, a substrate molecule (4-nitrophenol) and an FMN per protein chain, two ethylene glycols, a HEPES (buffer) molecule, a formic acid molecule, and 263 water molecules were found. The refinement of the structure of Hi KW20 NfsB against the 1.97-Å resolution data was converged to an Rwork of 0.184 and an Rfree of 0.217, and the structure comprises two protein chains with residues 2 to 220 and 3 to 220. In addition to the cofactor molecule FMN for each protein chain, an acetic acid and a chloride ion and 112 water molecules were also identified in the structure. For the Hi Int1 NfsB, the structure converged to an Rwork/Rfree of 0.171/0.216 at a resolution of 1.95 Å and consists of the dimer of two 220-residue protein molecules (1 to 220). The structure also includes an FMN/protein chain, two acetic acids, two ethylene glycols, a sulfate, and 171 water molecules. The structure of Hi 86-028NP NfsB has a resolution of 1.68 Å with an Rwork/Rfree of 0.152/0.191 and contains two dimers of four protein molecules with residues of 2 to 220, −2 to 220, 1 to 220, and −1 to 220 for the molecules A, B, C, and D, respectively, as well as an FMN for each chain, three ethylene glycols, two potassium, two calcium, and three chloride ions, and 358 water molecules. The structure of the NfsB homolog from Nm Z2491 was refined to Rwork and Rfree to 0.192 and 0.218 against the 1.75-Å data and consists of four protein molecules of 221 residues (1 to 221). Additionally, two ethylene glycols, four chloride ions, and 424 water molecules were found in the structure, and each protein chain contains an FMN and a nicotinic acid. The stereochemistry of the structures was checked with PROCHECK , which were disordered in most of these structures. In all structures, each protein molecule contains a well-ordered FMN molecule, a cofactor, in the corresponding active site. The final structure of Hi 12 NfsB converged to PROCHECK  and the PROCHECK . The dat7LDQ, 7RZL, 7S14, 7RZP, 7S1A, and 6WT2.The atomic coordinates of the NfsB structures from Hi 12, Hi 12 complexed with 4-nitrophenol, Hi 86-028NP, Hi Int1, Hi KW20, and Nm Z2491 have been deposited in the PDB with the accession IDs


The function of collagen triple helix repeat containing 1 (CTHRC1) as an oncogene has been reported in a growing number of publications. Bioinformatics methods represent a beneficial approach to examine the mechanism and function of the CTHRC1 gene in the disease process of cancers from a pan-cancer perspective.In this study, using the online databases UCSC, NCBI, HPA, TIMER2, Oncomine, GEPIA, UALCAN, cBioPortal, COSMIC, MEXPRESS, STRING, CCLE, LinkedOmics, GTEx, TCGA, CGGA, and SangerBox, we focused on the relationship between CTHRC1 and tumorigenesis, progression, methylation, immunity, and prognosis. qPCR was used to detect CTHRC1 expression in glioma tissues and cell lines.The pan-cancer analysis showed that CTHRC1 was overexpressed in most tumors, and a significant correlation was observed between CTHRC1 expression and the prognosis of patients with cancer. CTHRC1 genetic alterations occur in diverse tumors and are associated with tumor progression. Levels of CTHRC1 promoter methylation were decreased in most cancer tissues compared with normal tissues. In addition, CTHRC1 coordinated the activity of ICP genes through diverse signal transduction pathways, was also associated with immune cell infiltration and the tumor microenvironment, and potentially represented a promising immunotherapy target. We identified CTHRC1-related genes across cancers using the GEPIA2 tool. The single-gene GO analysis of CTHRC1 across cancers showed that it was involved in some signaling pathways and biological processes, such as the Wnt signaling pathway, cell migration, and positive regulation of protein binding. The expression and function of CTHRC1 were also further verified in glioma tissues and cell lines.CTHRC1 is overexpressed in various cancer types and functions as an important oncogene that may promote tumorigenesis and development through different mechanisms. CTHRC1 may represent an important therapeutic target for human cancers.The online version contains supplementary material available at 10.1186/s12935-021-02266-3. Finally, we observed the available CTHRC1-binding proteins.By searching the STRING website (db.org/) , we querThe top 10 CTHRC1-correlated targeting genes in TCGA tumor and normal tissues were obtained using the “Similar Gene Detection” function of GEPIA2. Subsequently, a Pearson correlation analysis of CTHRC1 and these 10 genes was performed by applying the “correlation analysis” module of GEPIA2. The correlation coefficient (R) and the P-value were generated. The log2 TPM was used to generate the scatter plot. Moreover, by applying the “Gene_Corr” function of TIMER2, we obtained a heatmap of these top 10 targeting genes.http://www.linkedomics.org/login.php) [The LinkedOmics database (gin.php)  was usedAll clinical samples were collected from patients with primary glioma who underwent surgery at the First Affiliated Hospital of Zhengzhou University. A microscopic examination of each sample confirmed ≥ 80% tumor cells. These samples were quickly stored in liquid nitrogen. According to the WHO criteria, the neuropathologist verified the pathological grade of each tissue sample. These glioma specimens included 19 grade II gliomas, 9 grade III gliomas, and 15 grade IV gliomas. Detailed information on the glioma samples is provided in Additional file 2 at 37 °C.Human astrocytes and human glioma cell lines  were obtained from ATCC . Through the ATCC cell line authentication service, cell lines were tested, and mycoplasma was also routinely tested. Human astrocytes were grown in astrocyte medium (AM)  supplemented with 10 mL of fetal bovine serum (FBS) , 5 mL of Astrocyte Growth Supplement (AGS)  and 5 mL of penicillin/streptomycin solution (P/S) . Human glioma cell lines were maintained in Dulbecco’s modified Eagle’s medium (DMEM) supplemented with 10% FBS . All cell lines were grown in a humidified incubator with 5% CO−ΔΔCT method. A t test was used for statistical analyses, and P < 0.05 was considered statistically significant.Total RNA was extracted from glioma tissues and cell lines using TRIzol reagent . Using a reverse transcription kit , the RNA (3 μg) was reverse transcribed into cDNAs with a reverse transcription system of 20 μL. Quantitative polymerase chain reaction (qPCR) was conducted using 2 × SYBR Green qPCR Master Mix (Low ROX) . The reaction mixture volume was 20 μL, including 10 μL of 2 × SYBR Green qPCR Master Mix (Low ROX), 6 μL of nuclease-free water, 0.2 μM of each primer and 2 μL of cDNA products. The PCR cycling conditions were as follows: 95 °C for 3 min, 95 °C for 15 s, and 60 °C for 40 s for 1 cycle and 95 °C for 15 s, 60 °C for 1 min, and 95 °C for 1 s for 40 cycles followed by the melting curve stage. Relative gene expression was obtained using the 2The following primer sequences were used:GAPDHForward: 5′-GGTGGTCTCCTCTGACTTCAACA-3′,Reverse: 5′-GTTGCTGTAGCCAAATTCGTTGT-3’,CTHRC1Forward: 5′-GGACCAAGGAAGCCCTGAAAT-3’, and.Reverse: 5’-AGCAACATCCACTAATCCAGCA-3’.The relative standard curve method was used to analyze the data, which were normalized to GAPDH.The HR and P-value were used to evaluate the significance of differences in survival. Pearson’s correlation coefficient and statistical significance were used to assess the associations of gene expression, and the absolute value was used to determine the strength of the correlation. The results were regarded as statistically significant at *P < 0.05, **P < 0.01 and ***P < 0.001.The analysis process is shown in Additional file We first performed an analysis of the pattern of CTHRC1 expression in various normal tissues and tumor/nontumor cells. As shown in Fig. We analyzed the differences of CTHRC1 mRNA expression levels in different cancer and normal tissues using the Oncomine database. The CTHRC1 expression level was enhanced in brain and CNS cancer, breast cancer, cervical cancer, colorectal cancer, esophageal cancer, gastric cancer, head and neck cancer, kidney cancer, liver cancer, lung cancer, ovarian cancer, pancreatic cancer, prostate cancer and leukemia, lymphoma and melanoma tumors compared to normal tissues , but was not associated with PPS P = 0.36), RFS (P = 0.06) and OS (P = 0.34) of patients with breast cancer  datasets Fig. d. TherefTumor-infiltrating immune cells are the primary components of the tumor microenvironment and exert important effects on the initiation, progression or metastasis of cancer , 42. TheFor instance, the CTHRC1 expression level was linked to high level of immune cell infiltration in LIHC and COAD Fig. a and a pWe then examined the potential correlations between CTHRC1 gene expression and the level of infiltration of different immune cells in various cancers using the TIMER2 portal. Based on all or most algorithms, CTHRC1 expression negatively correlated with the immune infiltration of CD8 + T cells in CESC, DLBC, HNSC, HNSC-HPV + , KIRC, SKCM, and SKCM metastasis Fig. b. A posiAs predictors of the therapeutic efficacy of tumor immunotherapy, antitumor immunity is correlated with MSI in the tumor microenvironment . We subsICP genes play an important role in immune cell infiltration and immunotherapy . TherefoWe continued to examine the relationship between CTHRC1 expression and immune cells. As shown in Additional file Using the STRING tool, we screened the CTHRC1-binding proteins to identify the potential role of the CTHRC1 gene in tumor pathogenesis. We first screened 7 CTHRC1-binding proteins based on experimental and dataset evidence. The interaction network of FZD6, FZD5, WNT3A, ROR2, DVL1, DVL2 and DVL3 is displayed in Fig. Staphylococcus aureus infection, complement and coagulation cascades, phosphatidylinositol signaling system, glutamatergic synapse, butanoate metabolism, and other pathways , as well as the pathways and functions involved. The heatmap shows the top 50 significant genes that were positively and negatively correlated with CTHRC1  than in LGG tissue samples (n = 19) Fig. a, b. SimAs an important component of the Wnt signaling pathway, CTHRC1 has been suggested to be involved in the biogenesis and progression of various cancers and is distinctly linked to the immune cell infiltration , 45, 46.We first explored CTHRC1 expression levels and found that CTHRC1 mRNA was overexpressed in most tumors, compared with adjacent normal tissues Fig. d, e, wasIt is widely accepted that cancers are triggered by gene mutations . Orloff Aberrant DNA methylation is associated with oncogenesis –40, 54. The role of immunity in tumorigenesis has been widely identified –60. It hFinally, to analyze the function of CTHRC1 in cancers, an enrichment analysis of CTHRC1-related genes and proteins was performed. We obtained 7 CTHRC1-binding proteins and constructed their interaction network ; c Expression levels of the CTHRC1 mRNA in different pathological stages of ACC, BLCA, ESCA, KICH, KIRC, KIRP, LUSC, PAAD, STAD, THCA.Additional file 3: Figure S3. CTHRC1 mRNA expression in glioma of different grades and a single-gene GO analysis of CTHRC1. a The expression levels of CTHRC1 mRNA were analyzed in normal brain and glioma tissues of different grades from GTEx and TCGA databases; b The expression levels of CTHRC1 mRNA were analyzed in glioma of different grades in CGGA cohort ; (c) CTHRC1 expression is positively associated with each analysis result.Additional file 4: Figure S4. The immunohistochemical staining, protein expression level and prognosis of CTHRC1 protein in different tumors. a Immunohistochemical staining of CTHRC1 protein in renal, liver, colorectal, prostate, lung and breast cancers, and correlation between CTHRC1 protein expression and survival prognosis of these cancers. b The level of CTHRC1 protein is higher in ovarian, breast and colon cancers, and clear cell RCC, UCEC, LUAD than in adjacent normal tissues. Z-values represent standard deviations from the median across samples for the given cancer type. Log2 Spectral count ratio values from CPTAC were firstly normalized within each sample profile, then normalized across samples.Additional file 5: Figure S5. Correlation between CTHRC1 mRNA expression and survival prognosis of cancers in TCGA. We used the GEPIA2 tool to perform overall survival a and disease-free survival b analyses of different tumors in TCGA by CTHRC1 gene expression. The survival map and Kaplan–Meier curves with positive results are given.Additional file 6: Figure S6. Correlation between CTHRC1 mRNA expression and survival prognosis. The relationships between CTHRC1 expression and DFI a or DSS b prognosis of different cancers in “Gene-KM plotter” module of SangerBox; (c) A Kaplan–Meier survival curve was used to examine the expression of CTHRC1 on the all WHO grade primary glioma, WHO grade III, WHO grade IV primary glioma and HGG primary glioma survival in the CGGA cohort .Additional file 7: Figure S7. CTHRC1 mutation analysis. The main mutation type a and mutation sites b of CTHRC1 were analyzed via COMIC database. c The primary SNV class type was G > A.Additional file 8: Figure S8. CTHRC1 alteration in UCEC. a Lollipop plot displaying mutation distribution and protein domains for CTHRC1 in cancer with the labeled recurrent hotspots. Somatic mutation rate and transcript names are indicated by plot title and subtitle, respectively. b Oncoplot displaying the somatic landscape of UCEC cohort. Genes are ordered by their mutation frequency, and samples are ordered according to disease histology as indicated by the annotation bar (bottom). Side bar plot shows log10 transformed Q-values estimated by MutSigCV. Landscape of mutation profiles in UCEC samples. Mutation information of each gene in each sample was shown in the waterfall plot, where different colors with specific annotations at the bottom meant the various mutation types. The barplot above the legend exhibited the number of mutation burden. According to UCEC samples, cohort summary plot displaying distribution of variants according to variant classification (c), variant classification type d) and SNV class e. Bottom part indicates mutation load for each sample (f), variant type (g); A stacked barplot shows top ten mutated genes (h).Additional file 9: Figure S9. Correlation of CTHRC1 expression with immune infiltration level in diverse type cancers via TIMER database. Gene expression levels against tumor purity is displayed on the left-most panel. The correlation of CTHRC1 expression with the abundance of immune infiltrates, including B cells, CD4 + T cells, CD8 + T cells, neutrophils, macrophages, and dendritic cells is displayed on the other panels.Additional file 10: Figure S10. Gene-immune analysis of CTHCR1. The relationship between CTHRC1 expression and infiltrating levels of B cells, CD4 + T cells, CB8 + T cells, macrophages, neutrophils, dendritic cell (a), MSI (b), ESTIMATE score (c), ICP genes (d); and Immune cells (e) in human cancers. * P < 0.05; ** P < 0.01; *** P < 0.001.Additional file 11: Figure S11. CTHRC1 coexpression genes in glioma from LinkedOmics. Heat maps showing top 50 genes positively a and negatively b correlated with CTHRC1 in glioma. Significantly enriched KEGG pathways c and GO annotations d of CTHRC1 coexpression genes in glioma.Additional file 12: Table S1. Clinical data of glioma patients. Table S2. CTHRC1 expression in cancers and normal tissue in Oncomine database. Table S3. CTHRC1 single-gene GO analysis in SangerBox database.Additional file 13. CTHRC1 alteration details of cancer type, protein change, mutation type.