As essential components of ionic polymer electrolytes (IPEs), ionic liquids (ILs) with high ionic conductivity and wide electrochemical window are promising candidates to enable safe and high-energy-density lithium metal batteries (LMBs). Here, we describe a machine learning workflow embedded with quantum calculation and graph convolutional neural network to discover potential ILs for IPEs. By selecting subsets of the recommended ILs, combining with a rigid-rod polyelectrolyte and a lithium salt, we develop a series of thin (~50 μm) and robust (>200 MPa) IPE membranes. The Li|IPEs|Li cells exhibit ultrahigh critical-current-density (6 mA cm-2) at 80 °C. The Li|IPEs|LiFePO4 (10.3 mg cm-2) cells deliver outstanding capacity retention in 350 cycles (>96% at 0.5C; >80% at 2C), fast charge/discharge capability (146 mAh g-1 at 3C) and excellent efficiency (>99.92%). This performance is rarely reported by other single-layer polymer electrolytes without any flammable organics for LMBs.

Peptide identification in liquid chromatography-tandem mass spectrometry (LC-MS/MS) experiments relies on computational algorithms for matching acquired MS/MS spectra against sequences of candidate peptides using database search tools, such as MSFragger. Here, we present a new tool, MSBooster, for rescoring peptide-to-spectrum matches using additional features incorporating deep learning-based predictions of peptide properties, such as LC retention time, ion mobility, and MS/MS spectra. We demonstrate the utility of MSBooster, in tandem with MSFragger and Percolator, in several different workflows, including nonspecific searches (immunopeptidomics), direct identification of peptides from data independent acquisition data, single-cell proteomics, and data generated on an ion mobility separation-enabled timsTOF MS platform. MSBooster is fast, robust, and fully integrated into the widely used FragPipe computational platform.

Decarbonized power systems are critical to mitigate climate change, yet methods to achieve a reliable and resilient near-zero power system are still under exploration. This study develops an hourly power system simulation model considering high-resolution geological constraints for carbon-capture-utilization-and-storage to explore the optimal solution for a reliable and resilient near-zero power system. This is applied to 31 provinces in China by simulating 10,450 scenarios combining different electricity storage durations and interprovincial transmission capacities, with various shares of abated fossil power with carbon-capture-utilization-and-storage. Here, we show that allowing up to 20% abated fossil fuel power generation in the power system could reduce the national total power shortage rate by up to 9.0 percentages in 2050 compared with a zero fossil fuel system. A lowest-cost scenario with 16% abated fossil fuel power generation in the system even causes 2.5% lower investment costs in the network (or $16.8 billion), and also increases system resilience by reducing power shortage during extreme climatic events.

Cetuximab therapy is the major treatment for colorectal cancer (CRC), but drug resistance limits its effectiveness. Here, we perform longitudinal and deep proteomic profiling of 641 plasma samples originated from 147 CRC patients (CRCs) undergoing cetuximab therapy with multi-course treatment, and 90 healthy controls (HCs). COL12A1, THBS2, S100A8, and S100A9 are screened as potential proteins to distinguish CRCs from HCs both in plasma and tissue validation cohorts. We identify the potential biomarkers (RRAS2, MMP8, FBLN1, RPTOR, and IMPDH2) for the initial response prediction. In a longitudinal setting, we identify two clusters with distinct fluctuations and construct the model with high accuracy to predict the longitudinal response, further validated in the independent cohort. This study reveals the heterogeneity of different biomarkers for tumor diagnosis, the initial and longitudinal response prediction respectively in the first course and multi-course cetuximab treatment, may ultimately be useful in monitoring and intervention strategies for CRC.

Mapping the chromatin occupancy of transcription factors (TFs) is a key step in deciphering developmental transcriptional programs. Here we use biotinylated knockin alleles of seven key cardiac TFs (GATA4, NKX2-5, MEF2A, MEF2C, SRF, TBX5, TEAD1) to sensitively and reproducibly map their genome-wide occupancy in the fetal and adult mouse heart. These maps show that TF occupancy is dynamic between developmental stages and that multiple TFs often collaboratively occupy the same chromatin region through indirect cooperativity. Multi-TF regions exhibit features of functional regulatory elements, including evolutionary conservation, chromatin accessibility, and activity in transcriptional enhancer assays. H3K27ac, a feature of many enhancers, incompletely overlaps multi-TF regions, and multi-TF regions lacking H3K27ac retain conservation and enhancer activity. TEAD1 is a core component of the cardiac transcriptional network, co-occupying cardiac regulatory regions and controlling cardiomyocyte-specific gene functions. Our study provides a resource for deciphering the cardiac transcriptional regulatory network and gaining insights into the molecular mechanisms governing heart development.

Oncolytic virotherapy is a promising therapeutic strategy that uses replication-competent viruses to selectively destroy malignancies. However, the therapeutic effect of certain oncolytic viruses (OVs) varies among cancer patients. Thus, it is necessary to overcome resistance to OVs through rationally designed combination strategies. Here, through an anticancer drug screening, we show that DNA-dependent protein kinase (DNA-PK) inhibition sensitizes cancer cells to OV M1 and improves therapeutic effects in refractory cancer models in vivo and in patient tumour samples. Infection of M1 virus triggers the transcription of interferons (IFNs) and the activation of the antiviral response, which can be abolished by pretreatment of DNA-PK inhibitor (DNA-PKI), resulting in selectively enhanced replication of OV M1 within malignancies. Furthermore, DNA-PK inhibition promotes the DNA damage response induced by M1 virus, leading to increased tumour cell apoptosis. Together, our study identifies the combination of DNA-PKI and OV M1 as a potential treatment for cancers.

N6,2'-O-dimethyladenosine (m6Am), a terminal modification adjacent to the mRNA cap, is a newly discovered reversible RNA modification. Yet, a specific and sensitive tool to directly map transcriptome-wide m6Am is lacking. Here, we report m6Am-seq, based on selective in vitro demethylation and RNA immunoprecipitation. m6Am-seq directly distinguishes m6Am and 5'-UTR N6-methyladenosine (m6A) and enables the identification of m6Am at single-base resolution and 5'-UTR m6A in the human transcriptome. Using m6Am-seq, we also find that m6Am and 5'-UTR m6A respond dynamically to stimuli, and identify key functional methylation sites that may facilitate cellular stress response. Collectively, m6Am-seq reveals the high-confidence m6Am and 5'-UTR m6A methylome and provides a robust tool for functional studies of the two epitranscriptomic marks.

Macrophages are involved in tissue homeostasis and are critical for innate immune responses, yet distinct macrophage populations in different tissues exhibit diverse gene expression patterns and biological processes. While tissue-specific macrophage epigenomic and transcriptomic profiles have been reported, proteomes of different macrophage populations remain poorly characterized. Here we use mass spectrometry and bulk RNA sequencing to assess the proteomic and transcriptomic patterns, respectively, of 10 primary macrophage populations from seven mouse tissues, bone marrow-derived macrophages and the cell line RAW264.7. The results show distinct proteomic landscape and protein copy numbers between tissue-resident and recruited macrophages. Construction of a hierarchical regulatory network finds cell-type-specific transcription factors of macrophages serving as hubs for denoting tissue and functional identity of individual macrophage subsets. Finally, Il18 is validated to be essential in distinguishing molecular signatures and cellular function features between tissue-resident and recruited macrophages in the lung and liver. In summary, these deposited datasets and our open proteome server ( http://macrophage.mouseprotein.cn ) integrating all information will provide a valuable resource for future functional and mechanistic studies of mouse macrophages.

Oncolytic virus is an attractive anticancer agent that selectively lyses cancer through targeting cancer cells rather than normal cells. Although M1 virus is effective against several cancer types, certain cancer cells present low sensitivity to it. Here we identified that most of the components in the cholesterol biosynthesis pathway are downregulated after M1 virus infection. Further functional studies illustrate that mevalonate/protein farnesylation/ras homolog family member Q (RHOQ) axis inhibits M1 virus replication. Further transcriptome analysis shows that RHOQ knockdown obviously suppresses Rab GTPase and ATP-mediated membrane transporter system, which may mediate the antiviral effect of RHOQ. Based on this, inhibition of the above pathway significantly enhances the anticancer potency of M1 virus in vitro, in vivo, and ex vivo. Our research provides an intriguing strategy for the rational combination of M1 virus with farnesyl transferase inhibitors to enhance therapeutic efficacy.

The reconstruction of neural circuits from serial section electron microscopy (ssEM) images is being accelerated by automatic image segmentation methods. Segmentation accuracy is often limited by the preceding step of aligning 2D section images to create a 3D image stack. Precise and robust alignment in the presence of image artifacts is challenging, especially as datasets are attaining the petascale. We present a computational pipeline for aligning ssEM images with several key elements. Self-supervised convolutional nets are trained via metric learning to encode and align image pairs, and they are used to initialize iterative fine-tuning of alignment. A procedure called vector voting increases robustness to image artifacts or missing image data. For speedup the series is divided into blocks that are distributed to computational workers for alignment. The blocks are aligned to each other by composing transformations with decay, which achieves a global alignment without resorting to a time-consuming global optimization. We apply our pipeline to a whole fly brain dataset, and show improved accuracy relative to prior state of the art. We also demonstrate that our pipeline scales to a cubic millimeter of mouse visual cortex. Our pipeline is publicly available through two open source Python packages.

Ion channels are important therapeutic targets, but the discovery of ion channel drugs remains challenging due to a lack of assays that allow high-throughput screening in the physiological context. Here we report C. elegans phenotype-based methods for screening ion channel drugs. Expression of modified human ether-a-go-go-related gene (hERG) potassium channels in C. elegans results in egg-laying and locomotive defects, which offer indicators for screening small-molecule channel modulators. Screening in worms expressing hERGA561V, which carries a trafficking-defective mutation A561V known to associate with long-QT syndrome, identifies two functional correctors Prostratin and ingenol-3,20-dibenzoate. These compounds activate PKCε signaling and consequently phosphorylate S606 at the pore region of the channel to promote hERGA561V trafficking to the plasma membrane. Importantly, the compounds correct electrophysiological abnormalities in hiPSC-derived cardiomyocytes bearing a heterozygous CRISPR/Cas9-edited hERGA561V. Thus, we have developed an in vivo high-throughput method for screening compounds that have therapeutic potential in treating channelopathies.

Genomics-based neoantigen discovery can be enhanced by proteomic evidence, but there remains a lack of consensus on the performance of different quality control methods for variant peptide identification in proteogenomics. We propose to use the difference between accurately predicted and observed retention times for each peptide as a metric to evaluate different quality control methods. To this end, we develop AutoRT, a deep learning algorithm with high accuracy in retention time prediction. Analysis of three cancer data sets with a total of 287 tumor samples using different quality control strategies results in substantially different numbers of identified variant peptides and putative neoantigens. Our systematic evaluation, using the proposed retention time metric, provides insights and practical guidance on the selection of quality control strategies. We implement the recommended strategy in a computational workflow named NeoFlow to support proteogenomics-based neoantigen prioritization, enabling more sensitive discovery of putative neoantigens.

Release of promoter-proximally paused RNA polymerase II (RNAPII) is a recently recognized transcriptional regulatory checkpoint. The biological roles of RNAPII pause release and the mechanisms by which extracellular signals control it are incompletely understood. Here we show that VEGF stimulates RNAPII pause release by stimulating acetylation of ETS1, a master endothelial cell transcriptional regulator. In endothelial cells, ETS1 binds transcribed gene promoters and stimulates their expression by broadly increasing RNAPII pause release. 34 VEGF enhances ETS1 chromatin occupancy and increases ETS1 acetylation, enhancing its binding to BRD4, which recruits the pause release machinery and increases RNAPII pause release. Endothelial cell angiogenic responses in vitro and in vivo require ETS1-mediated transduction of VEGF signaling to release paused RNAPII. Our results define an angiogenic pathway in which VEGF enhances ETS1-BRD4 interaction to broadly promote RNAPII pause release and drive angiogenesis.Promoter proximal RNAPII pausing is a rate-limiting transcriptional mechanism. Chen et al. show that this process is essential in angiogenesis by demonstrating that the endothelial master transcription factor ETS1 promotes global RNAPII pause release, and that this process is governed by VEGF.

Zika virus (ZIKV) infection during pregnancy threatens pregnancy and fetal health. However, the infectivity and pathological effects of ZIKV on placental trophoblast progenitor cells in early human embryos remain largely unknown. Here, using human trophoblast stem cells (hTSCs), we demonstrated that hTSCs were permissive to ZIKV infection, and resistance to ZIKV increased with hTSC differentiation. Combining gene knockout and transcriptome analysis, we demonstrated that the intrinsic expression of AXL and TIM-1, and the absence of potent interferon (IFN)-stimulated genes (ISGs) and IFNs contributed to the high sensitivity of hTSCs to ZIKV. Furthermore, using our newly developed hTSC-derived trophoblast organoid (hTSC-organoid), we demonstrated that ZIKV infection disrupted the structure of mature hTSC-organoids and inhibited syncytialization. Single-cell RNA sequencing (scRNA-seq) further demonstrated that ZIKV infection of hTSC-organoids disrupted the stemness of hTSCs and the proliferation of cytotrophoblast cells (CTBs) and probably led to a preeclampsia (PE) phenotype. Overall, our results clearly demonstrate that hTSCs represent the major target cells of ZIKV, and a reduced syncytialization may result from ZIKV infection of early developing placenta. These findings deepen our understanding of the characteristics and consequences of ZIKV infection of hTSCs in early human embryos.

Maize unilateral cross-incompatibility (UCI) that causes non-Mendelian segregation ratios has been documented for more than a century. Ga1, Ga2, and Tcb1 are three major UCI systems, described but not fully understood. Here, we report comprehensive genetic studies on the Ga2 locus and map-based cloning of the tightly linked male determinant ZmGa2P and female determinant ZmGa2F that govern pollen-silk compatibility among different maize genotypes. Both determinants encode putative pectin methylesterases (PME). A significantly higher degree of methyl esterification is detected in the apical region of pollen tubes growing in incompatible silks. No direct interaction between ZmGa2P and ZmGa2F is detected in the yeast two-hybrid system implying a distinct mechanism from that of self-incompatibility (SI). We also demonstrate the feasibility of Ga2 as a reproductive barrier in commercial breeding programs and stacking Ga2 with Ga1 could strengthen the UCI market potentials.

Squamous cell carcinoma (SCC) and adenocarcinoma (AC) are two main histological subtypes of solid cancer; however, SCCs are derived from different organs with similar morphologies, and it is challenging to distinguish the origin of metastatic SCCs. Here we report a deep proteomic analysis of 333 SCCs of 17 organs and 69 ACs of 7 organs. Proteomic comparison between SCCs and ACs identifies distinguishable pivotal pathways and molecules in those pathways play consistent adverse or opposite prognostic roles in ACs and SCCs. A comparison between common and rare SCCs highlights lipid metabolism may reinforce the malignancy of rare SCCs. Proteomic clusters reveal anatomical features, and kinase-transcription factor networks indicate differential SCC characteristics, while immune subtyping reveals diverse tumor microenvironments across and within diagnoses and identified potential druggable targets. Furthermore, tumor-specific proteins provide candidates with differentially diagnostic values. This proteomics architecture represents a public resource for researchers seeking a better understanding of SCCs and ACs.

Although oxaliplatin-based chemotherapy has been effective in the treatment of hepatocellular carcinoma (HCC), primary or acquired resistance to oxaliplatin remains a major challenge in the clinic. Through functional screening using CRISPR/Cas9 activation library, transcriptomic profiling of clinical samples, and functional validation in vitro and in vivo, we identify PRMT3 as a key driver of oxaliplatin resistance. Mechanistically, PRMT3-mediated oxaliplatin-resistance is in part dependent on the methylation of IGF2BP1 at R452, which is critical for the function of IGF2BP1 in stabilizing the mRNA of HEG1, an effector of PRMT3-IGF2BP1 axis. Also, PRMT3 overexpression may serve as a biomarker for oxaliplatin resistance in HCC patients. Collectively, our study defines the PRTM3-IGF2BP1-HEG1 axis as important regulators and therapeutic targets in oxaliplatin-resistance and suggests the potential to use PRMT3 expression level in pretreatment biopsy as a biomarker for oxaliplatin-resistance in HCC patients.

Chemotherapy and targeted therapy are the major treatments for gastric cancer (GC), but drug resistance limits its effectiveness. Here, we profile the proteome of 206 tumor tissues from patients with GC undergoing either chemotherapy or anti-HER2-based therapy. Proteome-based classification reveals four subtypes (G-I-G-IV) related to different clinical and molecular features. MSI-sig high GC patients benefit from docetaxel combination treatment, accompanied by anticancer immune response. Further study reveals patients with high T cell receptor signaling respond to anti-HER2-based therapy; while activation of extracellular matrix/PI3K-AKT pathway impair anti-tumor effect of trastuzumab. We observe CTSE functions as a cell intrinsic enhancer of chemosensitivity of docetaxel, whereas TKTL1 functions as an attenuator. Finally, we develop prognostic models with high accuracy to predict therapeutic response, further validated in an independent validation cohort. This study provides a rich resource for investigating the mechanisms and indicators of chemotherapy and targeted therapy in GC.

As the unique cell type in articular cartilage, chondrocyte senescence is a crucial cellular event contributing to osteoarthritis development. Here we show that clathrin-mediated endocytosis and activation of Notch signaling promotes chondrocyte senescence and osteoarthritis development, which is negatively regulated by myosin light chain 3. Myosin light chain 3 (MYL3) protein levels decline sharply in senescent chondrocytes of cartilages from model mice and osteoarthritis (OA) patients. Conditional deletion of Myl3 in chondrocytes significantly promoted, whereas intra-articular injection of adeno-associated virus overexpressing MYL3 delayed, OA progression in male mice. MYL3 deficiency led to enhanced clathrin-mediated endocytosis by promoting the interaction between myosin VI and clathrin, further inducing the internalization of Notch and resulting in activation of Notch signaling in chondrocytes. Pharmacologic blockade of clathrin-mediated endocytosis-Notch signaling prevented MYL3 loss-induced chondrocyte senescence and alleviated OA progression in male mice. Our results establish a previously unknown mechanism essential for cellular senescence and provide a potential therapeutic direction for OA.

IDH1 mutations frequently occur early in human glioma. While IDH1 mutation has been shown to promote gliomagenesis via DNA and histone methylation, little is known regarding its regulation in antiviral immunity. Here, we discover that IDH1 mutation inhibits virus-induced interferon (IFN) antiviral responses in glioma cells. Mechanistically, D2HG produced by mutant IDH1 enhances the binding of DNMT1 to IRF3/7 promoters such that IRF3/7 are downregulated, leading to impaired type I IFN response in glioma cells, which enhances the susceptibility of gliomas to viral infection. Furthermore, we identify DNMT1 as a potential biomarker predicting which IDH1mut gliomas are most likely to respond to oncolytic virus. Finally, both D2HG and ectopic mutant IDH1 can potentiate the replication and oncolytic efficacy of VSVΔ51 in female mouse models. These findings reveal a pivotal role for IDH1 mutation in regulating antiviral response and demonstrate that IDH1 mutation confers sensitivity to oncolytic virotherapy.