Structure of the ER membrane complex, a transmembrane-domain insertase.

The endoplasmic reticulum (ER) membrane complex (EMC) cooperates with the Sec61 translocon to co-translationally insert a transmembrane helix (TMH) of many multi-pass integral membrane proteins into the ER membrane, and it is also responsible for inserting the TMH of some tail-anchored proteins1-3. How EMC accomplishes this feat has been unclear. Here we report the first, to our knowledge, cryo-electron microscopy structure of the eukaryotic EMC. We found that the Saccharomyces cerevisiae EMC contains eight subunits (Emc1-6, Emc7 and Emc10), has a large lumenal region and a smaller cytosolic region, and has a transmembrane region formed by Emc4, Emc5 and Emc6 plus the transmembrane domains of Emc1 and Emc3. We identified a five-TMH fold centred around Emc3 that resembles the prokaryotic YidC insertase and that delineates a largely hydrophilic client protein pocket. The transmembrane domain of Emc4 tilts away from the main transmembrane region of EMC and is partially mobile. Mutational studies demonstrated that the flexibility of Emc4 and the hydrophilicity of the client pocket are required for EMC function. The EMC structure reveals notable evolutionary conservation with the prokaryotic insertases4,5, suggests that eukaryotic TMH insertion involves a similar mechanism, and provides a framework for detailed understanding of membrane insertion for numerous eukaryotic integral membrane proteins and tail-anchored proteins.

Advancing single-cell RNA-seq data analysis through the fusion of multi-layer perceptron and graph neural network.

The advancement of single-cell sequencing technology has smoothed the ability to do biological studies at the cellular level. Nevertheless, single-cell RNA sequencing (scRNA-seq) data presents several obstacles due to the considerable heterogeneity, sparsity and complexity. Although many machine-learning models have been devised to tackle these difficulties, there is still a need to enhance their efficiency and accuracy. Current deep learning methods often fail to fully exploit the intrinsic interconnections within cells, resulting in unsatisfactory results. Given these obstacles, we propose a unique approach for analyzing scRNA-seq data called scMPN. This methodology integrates multi-layer perceptron and graph neural network, including attention network, to execute gene imputation and cell clustering tasks. In order to evaluate the gene imputation performance of scMPN, several metrics like cosine similarity, median L1 distance and root mean square error are used. These metrics are utilized to compare the efficacy of scMPN with other existing approaches. This research utilizes criteria such as adjusted mutual information, normalized mutual information and integrity score to assess the efficacy of cell clustering across different approaches. The superiority of scMPN over current single-cell data processing techniques in cell clustering and gene imputation investigations is shown by the experimental findings obtained from four datasets with gold-standard cell labels. This observation demonstrates the efficacy of our suggested methodology in using deep learning methodologies to enhance the interpretation of scRNA-seq data.

Structures and Electron Transport Paths in the Four Families of Flavin-Based Electron Bifurcation Enzymes.

Oxidoreductases facilitating electron transfer between molecules are pivotal in metabolic pathways. Flavin-based electron bifurcation (FBEB), a recently discovered energy coupling mechanism in oxidoreductases, enables the reversible division of electron pairs into two acceptors, bridging exergonic and otherwise unfeasible endergonic reactions. This chapter explores the four distinct FBEB complex families and highlights a decade of structural insights into FBEB complexes. In this chapter, we discuss the architecture, electron transfer routes, and conformational changes across all FBEB families, revealing the structural foundation that facilitate these remarkable functions.

The Saccharomyces cerevisiae Yta7 ATPase hexamer contains a unique bromodomain tier that functions in nucleosome disassembly.

The Saccharomyces cerevisiae Yta7 is a chromatin remodeler harboring a histone-interacting bromodomain (BRD) and two AAA+ modules. It is not well understood how Yta7 recognizes the histone H3 tail to promote nucleosome disassembly for DNA replication or RNA transcription. By cryo-EM analysis, here we show that Yta7 assembles a three-tiered hexamer with a top BRD tier, a middle AAA1 tier, and a bottom AAA2 tier. Unexpectedly, the Yta7 BRD stabilizes a four-stranded ß-helix, termed BRD-interacting motif (BIM), of the largely disordered N-terminal region. The BIM motif is unique to the baker's yeast, and we show both BRD and BIM contribute to nucleosome recognition. We found that Yta7 binds both acetylated and nonacetylated H3 peptides but with a higher affinity for the unmodified peptide. This property is consistent with the absence of key residues of canonical BRDs involved in acetylated peptide recognition and the role of Yta7 in general nucleosome remodeling. Interestingly, the BRD tier exists in a spiral and a flat-ring form on top of the Yta7 AAA+ hexamer. The spiral is likely in a nucleosome-searching mode because the bottom BRD blocks the entry to the AAA+ chamber. The flat ring may be in a nucleosome disassembly state because the entry is unblocked and the H3 peptide has entered the AAA+ chamber and is stabilized by the AAA1 pore loops 1 and 2. Indeed, we show that the BRD tier is a flat ring when bound to the nucleosome. Overall, our study sheds light on the nucleosome disassembly by Yta7.

Overcoming Challenges: Extending Cycle Life of Aqueous Zinc-Ion Batteries at High Zinc Utilization through a Synergistic Strategy.

Aqueous zinc-ion batteries (AZIBs) face challenges in achieving high energy density compared to conventional lithium-ion batteries (LIBs). The lower operating voltage and excessive Zn metal as anode pose constraints on the overall energy storage capacity of these batteries. An effective approach is to reduce the thickness of the Zn metal anode and control its mass appropriately. However, under the condition of using a thin Zn anode, the performance of AZIBs is often unsatisfactory. Through experiments and computational simulations, the electrode structural change and the formation of dead Zn as the primary reasons for the failure of batteries under a high Zn utilization rate are identified. Based on this understanding, a universal synergistic strategy that combines Cu foil current collectors and electrolyte additives to maintain the structural and thermodynamic stability of the Zn anode under a high Zn utilization rate (ZUR) is proposed. Specifically, the Cu current collectors can ensure that the Zn anode structure remains intact based on the spontaneous filling effect, while the additives can suppress parasitic side reactions at the interface. Ultimately, the symmetric cell demonstrates a cycling duration of 900 h at a 70% ZU, confirming the effectiveness of this strategy.

Atomic Zn-Doping Induced Sabatier Optimum in NiZn0.03 Catalyst for CO2 Electroreduction at Industrial-Level Current Densities.

The Sabatier principle defines the essential criteria for an ideal catalyst in heterogeneous catalysis, while reaching the Sabatier optimum is still challenging in catalyst design. Herein, an elegant strategy is described to reach the Sabatier optimum of Ni electrocatalyst in CO2 reduction reaction (CO2 RR) by atomically Zn doping. The incorporation of 3% Zn single atom into Ni lattice leads to the moderate degrade of d-band center via Ni-Zn electronic coupling, which balances the bonding strengths of *COOH and *CO, resulting in a relative low energy barrier for CO2 activation while not being substantially poisoned by CO. Consequently, NiZn0.03 /C exhibits unique catalytic activity (jCO >100 mA cm-2 at -0.6 V), wide potential range for selective CO production (FECO >90% from -0.65 to -1.15 V), and outstanding long-term stability (FECO >90% during 85 h electrolysis at -0.85 V). The results provide valuable insights for the rational fabrication of superior non-noble bimetallic electrocatalysts in CO2 electroreduction.

Molecular Orientation Regulation of Hole Transport Semicrystalline-Polymer Enables High-Performance Carbon-Electrode Perovskite Solar Cells.

Carbon-based perovskite solar cells (PSCs) coupled with solution-processed hole transport layers (HTLs) have shown potential owing to their combination of low cost and high performance. However, the commonly used poly(3-hexylthiophene) (P3HT) semicrystalline-polymer HTL dominantly shows edge-on molecular orientation, in which the alkyl side chains directly contact the perovskite layer, resulting in an electronically poor contact at the perovskite/P3HT interface. The study adopts a synergetic strategy comprising of additive and solvent engineering to transfer the edge-on molecular orientation of P3HT HTL into 3D molecular orientation. The target P3HT HTL possesses improved charge transport as well as enhanced moisture-repelling capability. Moreover, energy level alignment between target P3HT HTL and perovskite layer is realized. As a result, the champion devices with small (0.04 cm2) and larger areas (1 cm2) deliver notable efficiencies of 20.55% and 18.32%, respectively, which are among the highest efficiency of carbon-electrode PSCs.

Rapid identification of early infections in febrile patients after CD19 target CAR-T cell therapy for B-cell malignancies.

BACKGROUND: CD19-targeted chimeric antigen receptor T (CAR-T) cell therapy stands out as a revolutionary intervention, exhibiting remarkable remission rates in patients with refractory/relapsed (R/R) B-cell malignancies. However, the potential side effects of therapy, particularly cytokine release syndrome (CRS) and infections, pose significant challenges due to their overlapping clinical features. Promptly distinguishing between CRS and infection post CD19 target CAR-T cell infusion (CTI) remains a clinical dilemma. Our study aimed to analyze the incidence of infections and identify key indicators for early infection detection in febrile patients within 30 days post-CTI for B-cell malignancies. METHODS: In this retrospective cohort study, a cohort of 104 consecutive patients with R/R B-cell malignancies who underwent CAR-T therapy was reviewed. Clinical data including age, gender, CRS, ICANS, treatment history, infection incidence, and treatment responses were collected. Serum biomarkers procalcitonin (PCT), interleukin-6 (IL-6), and C-reactive protein (CRP) levels were analyzed using chemiluminescent assays. Statistical analyses employed Pearson's Chi-square test, t-test, Mann-Whitney U-test, Kaplan-Meier survival analysis, Cox proportional hazards regression model, Spearman rank correlation, and receiver operating characteristic (ROC) curve analysis to evaluate diagnostic accuracy and develop predictive models through multivariate logistic regression. RESULTS: In this study, 38 patients (36.5%) experienced infections (30 bacterial, 5 fungal, and 3 viral) within the first 30 days of CAR T-cell infusion. In general, bacterial, fungal, and viral infections were detected at a median of 7, 8, and 9 days, respectively, after CAR T-cell infusion. Prior allogeneic hematopoietic cell transplantation (HCT) was an independent risk factor for infection (Hazard Ratio [HR]: 4.432 [1.262-15.565], P = 0.020). Furthermore, CRS was an independent risk factor for both infection ((HR: 2.903 [1.577-5.345], P < 0.001) and severe infection (9.040 [2.256-36.232], P < 0.001). Serum PCT, IL-6, and CRP were valuable in early infection prediction post-CAR-T therapy, particularly PCT with the highest area under the ROC curve (AUC) of 0.897. A diagnostic model incorporating PCT and CRP demonstrated an AUC of 0.903 with sensitivity and specificity above 83%. For severe infections, a model including CRS severity and PCT showed an exceptional AUC of 0.991 with perfect sensitivity and high specificity. Based on the aforementioned analysis, we proposed a workflow for the rapid identification of early infection during CAR-T cell therapy. CONCLUSIONS: CRS and prior allogeneic HCT are independent infection risk factors post-CTI in febrile B-cell malignancy patients. Our identification of novel models using PCT and CRP for predicting infection, and PCT and CRS for predicting severe infection, offers potential to guide therapeutic decisions and enhance the efficacy of CAR-T cell therapy in the future.

Water-Soluble, Self-Healing, and Debonding Primer for the Interface between Silicone Leather and Polydimethylsiloxane Composites.

The exceptional hydrophobicity and antifouling properties of polydimethylsiloxane (PDMS) composites have attracted extensive interest as a result of low surface energy. However, PDMS composites are hardly bound by common primers, greatly limiting their practical applications. To address this issue, an EPMS/VTMS (EV) primer synthesized by hydrolytic polycondensation of 3-[(2,3)-epoxypropoxypropyl]methyldiethoxysilane (EPMS) and vinyltrimethoxysilane (VTMS) in acidic conditions is proposed. Interestingly, the EV primer exhibits exceptional reactivity, self-healing capabilities, and strong adhesion to various substrates, including metals, plastics, and glass. The bonding aluminum plates are easily debonded by immersion in water without any residue left. Subsequently, the EV primer has been applied to the interface between silicone leather and the PDMS composite. Results show that the bonding strength for the silicone leather coated with the EV/PDMS composite is 16 times higher than that of the silicone leather modified with the PDMS composite. Meanwhile, the modified silicone leather exhibits impressive antifouling performance, including aqueous and oily stains, appreciable breathability, and excellent wear resistance, even if suffering from 20 000 cycles of abrasion. These excellent advantages for the modified silicone leather should be attributable to the synergistic effect of the EV primer and the PDMS composite. These findings pave the way to develop an ecofriendly debonding primer for PDMS composites, greatly facilitating applications of silicone leather.

Dissection of the antitumor mechanism of tetrandrine based on metabolite profiling and network pharmacology.

RATIONALE: Tetrandrine, the Q-marker in Stephaniae Tetrandrae Radix, was proven to present an obvious antitumor effect. Until now, the metabolism and antitumor mechanism of tetrandrine have not been fully elucidated. METHODS: The metabolites of tetrandrine in rats were profiled using ultra-high-performance liquid chromatography coupled with time-of-flight mass spectrometry. The potential antitumor mechanism of tetrandrine in vivo was predicted using network pharmacology. RESULTS: A total of 30 metabolites were characterized in rats after ingestion of tetrandrine (10 mg/kg), including 0 in plasma, 7 in urine, 11 in feces, 9 in liver, 8 in spleen, 4 in lung, 5 in kidney, 5 in heart, and 4 in brain. This study was the first to show the metabolic processes demethylation, hydroxylation, and carbonylation in tetrandrine. The pharmacology network results showed that tetrandrine and its metabolites could regulate AKT1, TNF, MMP9, MMP2, PAK1, and so on by involving in proteoglycan tumor pathway, PI3K-Akt signaling pathway, tumor pathway, MAPK signaling pathway, and Rap1 signaling pathway. CONCLUSIONS: The metabolism features of tetrandrine and its potential antitumor mechanism were summarized, providing data for further pharmacological validation.

Dissection of potential anti-osteoporosis mechanism of isopsoralen - a quality control marker in Psoraleae Fructus - by metabolite profiling and network pharmacology.

RATIONALE: Isopsoralen (ISO), a quality control marker (Q-marker) in Psoraleae Fructus, is proven to present an obvious anti-osteoporosis effect. Until now, the metabolism and anti-osteoporosis mechanisms of ISO have not been fully elucidated, greatly restricting its drug development. METHODS: The metabolites of ISO in rats were profiled by using ultrahigh-performance liquid chromatography coupled with time-of-flight mass spectrometry. The potential anti-osteoporosis mechanism of ISO in vivo was predicted by using network pharmacology. RESULTS: A total of 15 metabolites were characterized in rats after ingestion of ISO (20 mg/kg/day, by gavage), including 2 in plasma, 12 in urine, 6 in feces, 1 in heart, 3 in liver, 1 in spleen, 1 in lung, 3 in kidney, and 2 in brain. The pharmacology network results showed that ISO and its metabolites could regulate AKT1, SRC, NFKB1, EGFR, MAPK3, etc., involved in the prolactin signaling pathway, ErbB signaling pathway, thyroid hormone pathway, and PI3K-Akt signaling pathway. CONCLUSIONS: This is the first time for revealing the in vivo metabolism features and potential anti-osteoporosis mechanism of ISO by metabolite profiling and network pharmacology, providing data for further verification of pharmacological mechanism.

Characterization of metabolic features and potential anti-osteoporosis mechanism of pinoresinol diglucoside using metabolite profiling and network pharmacology.

RATIONALE: Eucommia cortex is the core herb in traditional Chinese medicine preparations for the treatment of osteoporosis. Pinoresinol diglucoside (PDG), the quality control marker and the key pharmacodynamic component in Eucommia cortex, has attracted global attention because of its definite effects on osteoporosis. However, the in vivo metabolic characteristics of PDG and its anti-osteoporotic mechanism are still unclear, restricting its development and application. METHODS: Ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry was used to analyze the metabolic characteristics of PDG in rats, and its anti-osteoporosis targets and mechanism were predicted using network pharmacology. RESULTS: A total of 51 metabolites were identified or tentatively characterized in rats after oral administration of PDG (10 mg/kg/day), including 9 in plasma, 28 in urine, 13 in feces, 10 in liver, 4 in heart, 3 in spleen, 11 in kidneys, and 5 in lungs. Furan-ring opening, dimethoxylation, glucuronidation, and sulfation were the main metabolic characteristics of PDG in vivo. The potential mechanism of PDG against osteoporosis was predicted using network pharmacology. PDG and its metabolites could regulate BCL2, MARK3, ALB, and IL6, involving PI3K-Akt signaling pathway, estrogen signaling pathway, and so on. CONCLUSIONS: This study was the first to demonstrate the metabolic characteristics of PDG in vivo and its potential anti-osteoporosis mechanism, providing the data for further pharmacological validation of PDG in the treatment of osteoporosis.

Conversion of Carbon Dioxide into a Series of CBxOy- Compounds Mediated by LaB3,4O2- Anions: Synergy of the Electron Transfer and Lewis Pair Mechanisms to Construct B-C Bonds.

Converting CO2 into value-added products containing B-C bonds is a great challenge, especially for multiple B-C bonds, which are versatile building blocks for organoborane chemistry. In the condensed phase, the B-C bond is typically formed through transition metal-catalyzed direct borylation of hydrocarbons via C-H bond activation or transition metal-catalyzed insertion of carbenes into B-H bonds. However, excessive amounts of powerful boryl reagents are required, and products containing B-C bonds are complex. Herein, a novel method to construct multiple B-C bonds at room temperature is proposed by the gas-phase reactions of CO2 with LaBmOn- (m = 1-4, n = 1 or 2). Mass spectrometry and density functional theory calculations are applied to investigate these reactions, and a series of new compounds, CB2O2-, CB3O3-, and CB3O2-, which possess B-C bonds, are generated in the reactions of LaB3,4O2- with CO2. When the number of B atoms in the clusters is reduced to 2 or 1, there is only CO-releasing channel, and no CBxOy- compounds are released. Two major factors are responsible for this quite intriguing reactivity: (1) Synergy of electron transfer and boron-boron Lewis acid-base pair mechanisms facilitates the rupture of C═O double bond in CO2. (2) The boron sites in the clusters can efficiently capture the newly formed CO units in the course of reactions, favoring the formation of B-C bonds. This finding may provide fundamental insights into the CO2 transformation driven by clusters containing lanthanide atoms and how to efficiently build B-C bonds under room temperature.

Activation and Transformation of Methane on Boron-Doped Cobalt Oxide Cluster Cations CoBO2.

The cleavage of inert C-H bonds in methane at room temperature and the subsequent conversion into value-added products are quite challenging. Herein, the reactivity of boron-doped cobalt oxide cluster cations CoBO2+ toward methane under thermal collision conditions was studied by mass spectrometry experiments and quantum-chemical calculations. In this reaction, one H atom and the CH3 unit of methane were transformed separately to generate the product metaboric acid (HBO2) and one CoCH3+ ion, respectively. Theoretical calculations strongly suggest that a catalytic cycle can be completed by the recovery of CoBO2+ through the reaction of CoCH3+ with sodium perborate (NaBO3), and this reaction generates sodium methoxide (CH3ONa) as the other value-added product. This study shows that boron-doped cobalt oxide species are highly reactive to facilitate thermal methane transformation and may open a way to develop more effective approaches for methane (CH4) activation and conversion under mild conditions.

Single-cell RNA-seq data analysis based on directed graph neural network.

Single-cell RNA sequencing (scRNA-seq) data scale surges with high-throughput sequencing technology development. However, although single-cell data analysis is a powerful tool, various issues have been reported, such as sequencing sparsity and complex differential patterns in gene expression. Statistical or traditional machine learning methods are inefficient, and the accuracy needs to be improved. The methods based on deep learning can not directly process non-Euclidean spatial data, such as cell diagrams. In this study, we have developed graph autoencoders and graph attention network for scRNA-seq analysis based on a directed graph neural network named scDGAE. Directed graph neural networks cannot only retain the connection properties of the directed graph but also expand the receptive field of the convolution operation. Cosine similarity, median L1 distance, and root-mean-squared error are used to measure the gene imputation performance of different methods with scDGAE. Furthermore, adjusted mutual information, normalized mutual information, completeness score, and Silhouette coefficient score are used to measure the cell clustering performance of different methods with scDGAE. Experiment results show that the scDGAE model achieves promising performance in gene imputation and cell clustering prediction on four scRNA-seq data sets with gold-standard cell labels. Furthermore, it is a robust framework that can be applied to general scRNA-Seq analyses.

Nitrogen adsorption on Nb2C6H4+ cations: the important role of benzyne (ortho-C6H4).

N2 adsorption is a prerequisite for activation and transformation. Time-of-flight mass spectrometry experiments show that the Nb2C6H4+ cation, resulting from the gas-phase reaction of Nb2+ with C6H6, is more favorable for N2 adsorption than Nb+ and Nb2+ cations. Density functional theory calculations reveal the effect of the ortho-C6H4 ligand on N2 adsorption. In Nb2C6H4+, interactions between the Nb-4d and C-2p orbitals enable the Nb2+ cation to form coordination bonds with the ortho-C6H4 ligand. Although the ortho-C6H4 ligand in Nb2C6H4+ is not directly involved in the reaction, its presence increases the polarity of the cluster and brings the highest occupied molecular orbital (HOMO) closer to the lowest occupied molecular orbital (LUMO) of N2, thereby increasing the N2 adsorption energy, which effectively facilitates N2 adsorption and activation. This study provides fundamental insights into the mechanisms of N2 adsorption in "transition metal-organic ligand" systems.

Leadless pacemaker implantation using halo-shape technique in a severe dextroscoliosis octogenarian.

The halo-shape technique (HST) is an emerging approach for implanting a leadless pacemaker in scoliosis patients in recent years. Severe scoliosis and humpback made it challenging to push the tip of the delivery catheter towards the ventricular septum using the conventional gooseneck-shape technique. The feasibility and safety of the use of HST in an octogenarian with severe dextroscoliosis and humpback have not been well-assessed. Here, we report a case of high-degree atrioventricular block octogenarian with severe dextroscoliosis and humpback who successfully received a leadless pacemaker implantation using HST. Procedure-related complications were not observed, and the electrical parameters were stable at 6-month follow-up.

Manipulating Reactivity of Ir(CH2)0-2+ Cations toward Dinitrogen at Room Temperature: A Unique Dependence on the Organic Ligand Structures.

Nitrogen (N2) activation at room temperature has long been a great challenge. Therefore, the rational design of reactive species to adsorb N2, which is a prerequisite for cleavage of the strong N≡N triple bond in industrial and biological processes, is highly desirable and meaningful. Herein, the N2 adsorption process is controlled by regulating the types and numbers of organic ligands, and the organic ligands are produced through the reactions of Ir+ with methane and ethane. CH4 molecules dissociate on the Ir+ cations to form Ir(CH2)1,2+. The reaction of Ir+ with C2H6 can generate HIrC2H3+, which is different from the structure of Ir(CH2)2+ obtained from Ir+/CH4. The reactivity order of N2 adsorption is Ir(CH2)2+ > HIrC2H3+ ≫ HIrCH+ ≈ Ir+ (almost inert under similar reaction conditions), indicating that different organic ligand structures affect reactivity dramatically. The main reason for this interesting reactivity difference is that the lowest unoccupied molecular orbital (LUMO) level of Ir(CH2)2+ is much closer to the highest occupied molecular orbital (HOMO) level of N2 than those of the other three systems. This study provides new insights into the adsorption of N2 on metal-organic ligand species, in which the organic ligand dominates the reactivity, and it discovers new clues in designing effective transition metal carbine species for N2 activation.

Ccp1 Homodimer Mediates Chromatin Integrity by Antagonizing CENP-A Loading.

CENP-A is a centromere-specific histone 3 variant essential for centromere specification. CENP-A partially replaces canonical histone H3 at the centromeres. How the particular CENP-A/H3 ratio at centromeres is precisely maintained is unknown. It also remains unclear how CENP-A is excluded from non-centromeric chromatin. Here, we identify Ccp1, an uncharacterized NAP family protein in fission yeast that antagonizes CENP-A loading at both centromeric and non-centromeric regions. Like the CENP-A loading factor HJURP, Ccp1 interacts with CENP-A and is recruited to centromeres at the end of mitosis in a Mis16-dependent manner. These data indicate that factors with opposing CENP-A loading activities are recruited to centromeres. Furthermore, Ccp1 also cooperates with H2A.Z to evict CENP-A assembled in euchromatin. Structural analyses indicate that Ccp1 forms a homodimer that is required for its anti-CENP-A loading activity. Our study establishes mechanisms for maintenance of CENP-A homeostasis at centromeres and the prevention of ectopic assembly of centromeres.

dbPTM in 2022: an updated database for exploring regulatory networks and functional associations of protein post-translational modifications.

Protein post-translational modifications (PTMs) play an important role in different cellular processes. In view of the importance of PTMs in cellular functions and the massive data accumulated by the rapid development of mass spectrometry (MS)-based proteomics, this paper presents an update of dbPTM with over 2 777 000 PTM substrate sites obtained from existing databases and manual curation of literature, of which more than 2 235 000 entries are experimentally verified. This update has manually curated over 42 new modification types that were not included in the previous version. Due to the increasing number of studies on the mechanism of PTMs in the past few years, a great deal of upstream regulatory proteins of PTM substrate sites have been revealed. The updated dbPTM thus collates regulatory information from databases and literature, and merges them into a protein-protein interaction network. To enhance the understanding of the association between PTMs and molecular functions/cellular processes, the functional annotations of PTMs are curated and integrated into the database. In addition, the existing PTM-related resources, including annotation databases and prediction tools are also renewed. Overall, in this update, we would like to provide users with the most abundant data and comprehensive annotations on PTMs of proteins. The updated dbPTM is now freely accessible at https://awi.cuhk.edu.cn/dbPTM/.