SUMOylation is enriched in the nuclear matrix and required for chromosome segregation.

As an important posttranslational modification, SUMOylation plays critical roles in almost all biological processes. Although it has been well-documented that SUMOylated proteins are mainly localized in the nucleus and have roles in chromatin-related processes, we showed recently that the SUMOylation machinery is actually enriched in the nuclear matrix rather than chromatin. Here, we provide compelling biochemical, cellular imaging and proteomic evidence that SUMOylated proteins are highly enriched in the nuclear matrix. We demonstrated that inactivation of SUMOylation by inhibiting SUMO-activating E1 enzyme or KO of SUMO-conjugating E2 enzyme UBC9 have only mild effect on nuclear matrix composition, indicating that SUMOylation is neither required for nuclear matrix formation nor for targeting proteins to nuclear matrix. Further characterization of UBC9 KO cells revealed that loss of SUMOylation did not result in significant DNA damage, but led to mitotic arrest and chromosome missegregation. Altogether, our study demonstrates that SUMOylated proteins are selectively enriched in the nuclear matrix and suggests a role of nuclear matrix in mediating SUMOylation and its regulated biological processes.

ImmCluster: an ensemble resource for immunology cell type clustering and annotations in normal and cancerous tissues.

Single-cell transcriptome has enabled the transcriptional profiling of thousands of immune cells in complex tissues and cancers. However, subtle transcriptomic differences in immune cell subpopulations and the high dimensionality of transcriptomic data make the clustering and annotation of immune cells challenging. Herein, we introduce ImmCluster (http://bio-bigdata.hrbmu.edu.cn/ImmCluster) for immunology cell type clustering and annotation. We manually curated 346 well-known marker genes from 1163 studies. ImmCluster integrates over 420 000 immune cells from nine healthy tissues and over 648 000 cells from different tumour samples of 17 cancer types to generate stable marker-gene sets and develop context-specific immunology references. In addition, ImmCluster provides cell clustering using seven reference-based and four marker gene-based computational methods, and the ensemble method was developed to provide consistent cell clustering than individual methods. Five major analytic modules were provided for interactively exploring the annotations of immune cells, including clustering and annotating immune cell clusters, gene expression of markers, functional assignment in cancer hallmarks, cell states and immune pathways, cell-cell communications and the corresponding ligand-receptor interactions, as well as online tools. ImmCluster generates diverse plots and tables, enabling users to identify significant associations in immune cell clusters simultaneously. ImmCluster is a valuable resource for analysing cellular heterogeneity in cancer microenvironments.

CellMarker 2.0: an updated database of manually curated cell markers in human/mouse and web tools based on scRNA-seq data.

CellMarker 2.0 (http://bio-bigdata.hrbmu.edu.cn/CellMarker or http://117.50.127.228/CellMarker/) is an updated database that provides a manually curated collection of experimentally supported markers of various cell types in different tissues of human and mouse. In addition, web tools for analyzing single cell sequencing data are described. We have updated CellMarker 2.0 with more data and several new features, including (i) Appending 36 300 tissue-cell type-maker entries, 474 tissues, 1901 cell types and 4566 markers over the previous version. The current release recruits 26 915 cell markers, 2578 cell types and 656 tissues, resulting in a total of 83 361 tissue-cell type-maker entries. (ii) There is new marker information from 48 sequencing technology sources, including 10X Chromium, Smart-Seq2 and Drop-seq, etc. (iii) Adding 29 types of cell markers, including protein-coding gene lncRNA and processed pseudogene, etc. Additionally, six flexible web tools, including cell annotation, cell clustering, cell malignancy, cell differentiation, cell feature and cell communication, were developed to analysis and visualization of single cell sequencing data. CellMarker 2.0 is a valuable resource for exploring markers of various cell types in different tissues of human and mouse.

CellTracer: a comprehensive database to dissect the causative multilevel interplay contributing to cell development trajectories.

During the complex process of tumour development, the unique destiny of cells is driven by the fine-tuning of multilevel features such as gene expression, network regulation and pathway activation. The dynamic formation of the tumour microenvironment influences the therapeutic response and clinical outcome. Thus, characterizing the developmental landscape and identifying driver features at multiple levels will help us understand the pathological development of disease in individual cell populations and further contribute to precision medicine. Here, we describe a database, CellTracer (http://bio-bigdata.hrbmu.edu.cn/CellTracer), which aims to dissect the causative multilevel interplay contributing to cell development trajectories. CellTracer consists of the gene expression profiles of 1 941 552 cells from 222 single-cell datasets and provides the development trajectories of different cell populations exhibiting diverse behaviours. By using CellTracer, users can explore the significant alterations in molecular events and causative multilevel crosstalk among genes, biological contexts, cell characteristics and clinical treatments along distinct cell development trajectories. CellTracer also provides 12 flexible tools to retrieve and analyse gene expression, cell cluster distribution, cell development trajectories, cell-state variations and their relationship under different conditions. Collectively, CellTracer will provide comprehensive insights for investigating the causative multilevel interplay contributing to cell development trajectories and serve as a foundational resource for biomarker discovery and therapeutic exploration within the tumour microenvironment.

LncTarD 2.0: an updated comprehensive database for experimentally-supported functional lncRNA-target regulations in human diseases.

An updated LncTarD 2.0 database provides a comprehensive resource on key lncRNA-target regulations, their influenced functions and lncRNA-mediated regulatory mechanisms in human diseases. LncTarD 2.0 is freely available at (http://bio-bigdata.hrbmu.edu.cn/LncTarD or https://lnctard.bio-database.com/). LncTarD 2.0 was updated with several new features, including (i) an increased number of disease-associated lncRNA entries, where the current release provides 8360 key lncRNA-target regulations, with 419 disease subtypes and 1355 lncRNAs; (ii) predicted 3312 out of 8360 lncRNA-target regulations as potential diagnostic or therapeutic biomarkers in circulating tumor cells (CTCs); (iii) addition of 536 new, experimentally supported lncRNA-target regulations that modulate properties of cancer stem cells; (iv) addition of an experimentally supported clinical application section of 2894 lncRNA-target regulations for potential clinical application. Importantly, LncTarD 2.0 provides RNA-seq/microarray and single-cell web tools for customizable analysis and visualization of lncRNA-target regulations in diseases. RNA-seq/microarray web tool was used to mining lncRNA-target regulations in both disease tissue samples and CTCs blood samples. The single-cell web tools provide single-cell lncRNA-target annotation from the perspectives of pan-cancer analysis and cancer-specific analysis at the single-cell level. LncTarD 2.0 will be a useful resource and mining tool for the investigation of the functions and mechanisms of lncRNA deregulation in human disease.

Shedding light on the hidden human proteome expands immunopeptidome in cancer.

Unrestrained cellular growth and immune escape of a tumor are associated with the incidental errors of the genome and transcriptome. Advances in next-generation sequencing have identified thousands of genomic and transcriptomic aberrations that generate variant peptides that assemble the hidden proteome, further expanding the immunopeptidome. Emerging next-generation sequencing technologies and a number of computational methods estimated the abundance of immune infiltration from bulk transcriptome have advanced our understanding of tumor microenvironments. Here, we will characterize several major types of tumor-specific antigens arising from single-nucleotide variants, insertions and deletions, gene fusion, alternative splicing, RNA editing and non-coding RNAs. Finally, we summarize the current state-of-the-art computational and experimental approaches or resources and provide an integrative pipeline for the identification of candidate tumor antigens. Together, the systematic investigation of the hidden proteome in cancer will help facilitate the development of effective and durable immunotherapy targets for cancer.

AgingBank: a manually curated knowledgebase and high-throughput analysis platform that provides experimentally supported multi-omics data relevant to aging in multiple species.

Discovering the biological basis of aging is one of the greatest remaining challenges for biomedical field. Work on the biology of aging has discovered a range of interventions and pathways that control aging rate. Thus, we developed AgingBank (http://bio-bigdata.hrbmu.edu.cn/AgingBank) which was a manually curated comprehensive database and high-throughput analysis platform that provided experimentally supported multi-omics data relevant to aging in multiple species. AgingBank contained 3771 experimentally verified aging-related multi-omics entries from studies across more than 50 model organisms, including human, mice, worms, flies and yeast. The records included genome (single nucleotide polymorphism, copy number variation and somatic mutation), transcriptome [mRNA, long non-coding RNA (lncRNA), microRNA (miRNA) and circular RNA (circRNA)], epigenome (DNA methylation and histone modification), other modification and regulation elements (transcription factor, enhancer, promoter, gene silence, alternative splicing and RNA editing). In addition, AgingBank was also an online computational analysis platform containing five useful tools (Aging Landscape, Differential Expression Analyzer, Data Heat Mapper, Co-Expression Network and Functional Annotation Analyzer), nearly 112 high-throughput experiments of genes, miRNAs, lncRNAs, circRNAs and methylation sites related with aging. Cancer & Aging module was developed to explore the relationships between aging and cancer. Submit & Analysis module allows users upload and analyze their experiments data. AginBank is a valuable resource for elucidating aging-related biomarkers and relationships with other diseases.

Identifying and characterizing drug sensitivity-related lncRNA-TF-gene regulatory triplets.

Recently, many studies have shown that lncRNA can mediate the regulation of TF-gene in drug sensitivity. However, there is still a lack of systematic identification of lncRNA-TF-gene regulatory triplets for drug sensitivity. In this study, we propose a novel analytic approach to systematically identify the lncRNA-TF-gene regulatory triplets related to the drug sensitivity by integrating transcriptome data and drug sensitivity data. Totally, 1570 drug sensitivity-related lncRNA-TF-gene triplets were identified, and 16 307 relationships were formed between drugs and triplets. Then, a comprehensive characterization was performed. Drug sensitivity-related triplets affect a variety of biological functions including drug response-related pathways. Phenotypic similarity analysis showed that the drugs with many shared triplets had high similarity in their two-dimensional structures and indications. In addition, Network analysis revealed the diverse regulation mechanism of lncRNAs in different drugs. Also, survival analysis indicated that lncRNA-TF-gene triplets related to the drug sensitivity could be candidate prognostic biomarkers for clinical applications. Next, using the random walk algorithm, the results of which we screen therapeutic drugs for patients across three cancer types showed high accuracy in the drug-cell line heterogeneity network based on the identified triplets. Besides, we developed a user-friendly web interface-DrugSETs (http://bio-bigdata.hrbmu.edu.cn/DrugSETs/) available to explore 1570 lncRNA-TF-gene triplets relevant with 282 drugs. It can also submit a patient's expression profile to predict therapeutic drugs conveniently. In summary, our research may promote the study of lncRNAs in the drug resistance mechanism and improve the effectiveness of treatment.

Revealing the contribution of somatic gene mutations to shaping tumor immune microenvironment.

Interaction between tumor cells and immune cells determined highly heterogeneous microenvironments across patients, leading to substantial variation in clinical benefits from immunotherapy. Somatic gene mutations were found not only to elicit adaptive immunity but also to influence the composition of tumor immune microenvironment and various processes of antitumor immunity. However, due to an incomplete view of associations between gene mutations and immunophenotypes, how tumor cells shape the immune microenvironment and further determine the clinical benefit of immunotherapy is still unclear. To address this, we proposed a computational approach, inference of mutation effect on immunophenotype by integrated gene set enrichment analysis (MEIGSEA), for tracing back the genomic factor responsible for differences in immunophenotypes. MEIGSEA was demonstrated to accurately identify the previous confirmed immune-associated gene mutations, and systematic evaluation in simulation data further supported its performance. We used MEIGSEA to investigate the influence of driver gene mutations on the infiltration of 22 immune cell types across 19 cancers from The Cancer Genome Atlas. The top associated gene mutations with infiltration of CD8 T cells, such as CASP8, KRAS and EGFR, also showed extensive impact on other immune components; meanwhile, immune effector cells shared critical gene mutations that collaboratively contribute to shaping distinct tumor immune microenvironment. Furthermore, we highlighted the predictive capacity of gene mutations that are positively associated with CD8 T cells for the clinical benefit of immunotherapy. Taken together, we present a computational framework to help illustrate the potential of somatic gene mutations in shaping the tumor immune microenvironment.

Asymmetric Cyclodextrin-Dimer-Involved Nanoassemblies by Selective Host-Guest Interactions: Concentration-Dependent Morphology Evolution and Light-Regulated Biomedical Applications.

Supramolecular assembly has attracted significant attention and has been applied to various applications. Herein, a ß-γ-CD dimer was synthesized to complex different guest molecules, including single-strand polyethylene glycol (PEG)-modified C60 (PEG-C60), photothermal conversion reagent (IR780), and dexamethasone (Dexa), according to the complexation constant-dependent specific selectivity. Spherical or cylindrical nanoparticles, monolayer or bilayer vesicles, and bilayer fusion vesicles were discovered in succession if the concentration of PEG-C60 was varied. Moreover, if near-infrared light was employed to irradiate these nanoassemblies, the thermo-induced morphological evolution, subsequent cargo release, photothermal effect, and singlet oxygen (1O2) generation were successfully achieved. The in vitro cell experiments confirmed that these nanoparticles possessed excellent biocompatibility in a normal environment and achieved superior cytotoxicity by light regulation. Such proposed strategies for the construction of multilevel structures with different morphologies can open a new window to obtain various host-guest functional materials and achieve further use for disease treatment.

The CSF1-CSF1R pathway in the trigeminal ganglion mediates trigeminal neuralgia via inflammatory responses in mice.

BACKGROUND: Trigeminal neuralgia (TN) is the most severe type of neuropathic pain. The trigeminal ganglion (TG) is a crucial target for the pathogenesis and treatment of TN. The colony-stimulating factor 1 (CSF1) - colony-stimulating factor 1 receptor (CSF1R) pathway regulates lower limb pain development. However, the effect and mechanism of the CSF1-CSF1R pathway in TG on TN are unclear. METHODS: Partial transection of the infraorbital nerve (pT-ION) model was used to generate a mouse TN model. Mechanical and cold allodynia were used to measure pain behaviors. Pro-inflammatory factors (IL-6, TNF-a) were used to measure inflammatory responses in TG. PLX3397, an inhibitor of CSF1R, was applied to inhibit the CSF1-CSF1R pathway in TG. This pathway was activated in naïve mice by stereotactic injection of CSF1 into the TG. RESULTS: The TN model activated the CSF1-CSF1R pathway in the TG, leading to exacerbated mechanical and cold allodynia. TN activated inflammatory responses in the TG manifested as a significant increase in IL-6 and TNF-a levels. After using PLX3397 to inhibit CSF1R, CSF1R expression in the TG declined significantly. Inhibiting the CSF1-CSF1R pathway in the TG downregulated the expression of IL-6 and TNF-α to reduce allodynia-related behaviors. Finally, mechanical allodynia behaviors were exacerbated in naïve mice after activating the CSF1-CSF1R pathway in the TG. CONCLUSIONS: The CSF1-CSF1R pathway in the TG modulates TN by regulating neuroimmune responses. Our findings provide a theoretical basis for the development of treatments for TN in the TG.

LncACTdb 3.0: an updated database of experimentally supported ceRNA interactions and personalized networks contributing to precision medicine.

LncACTdb 3.0 is a comprehensive database of experimentally supported interactions among competing endogenous RNA (ceRNA) and the corresponding personalized networks contributing to precision medicine. LncACTdb 3.0 is freely available at http://bio-bigdata.hrbmu.edu.cn/LncACTdb or http://www.bio-bigdata.net/LncACTdb. We have updated the LncACTdb 3.0 database with several new features, including (i) 5669 experimentally validated ceRNA interactions across 25 species and 537 diseases/phenotypes through manual curation of published literature, (ii) personalized ceRNA interactions and networks for 16 228 patients from 62 datasets in TCGA and GEO, (iii) sub-cellular and extracellular vesicle locations of ceRNA manually curated from literature and data sources, (iv) more than 10 000 experimentally supported long noncoding RNA (lncRNA) biomarkers associated with tumor diagnosis and therapy, and (v) lncRNA/mRNA/miRNA expression profiles with clinical and pathological information of thousands of cancer patients. A panel of improved tools has been developed to explore the effects of ceRNA on individuals with specific pathological backgrounds. For example, a network tool provides a comprehensive view of lncRNA-related, patient-specific, and custom-designed ceRNA networks. LncACTdb 3.0 will provide novel insights for further studies of complex diseases at the individual level and will facilitate the development of precision medicine to treat such diseases.

Vitexin inhibits APEX1 to counteract the flow-induced endothelial inflammation.

Vascular endothelial cells are exposed to shear stresses with disturbed vs. laminar flow patterns, which lead to proinflammatory vs. antiinflammatory phenotypes, respectively. Effective treatment against endothelial inflammation and the consequent atherogenesis requires the identification of new therapeutic molecules and the development of drugs targeting these molecules. Using Connectivity Map, we have identified vitexin, a natural flavonoid, as a compound that evokes the gene-expression changes caused by pulsatile shear, which mimics laminar flow with a clear direction, vs. oscillatory shear (OS), which mimics disturbed flow without a clear direction. Treatment with vitexin suppressed the endothelial inflammation induced by OS or tumor necrosis factor-α. Administration of vitexin to mice subjected to carotid partial ligation blocked the disturbed flow-induced endothelial inflammation and neointimal formation. In hyperlipidemic mice, treatment with vitexin ameliorated atherosclerosis. Using SuperPred, we predicted that apurinic/apyrimidinic endonuclease1 (APEX1) may directly interact with vitexin, and we experimentally verified their physical interactions. OS induced APEX1 nuclear translocation, which was inhibited by vitexin. OS promoted the binding of acetyltransferase p300 to APEX1, leading to its acetylation and nuclear translocation. Functionally, knocking down APEX1 with siRNA reversed the OS-induced proinflammatory phenotype, suggesting that APEX1 promotes inflammation by orchestrating the NF-κB pathway. Animal experiments with the partial ligation model indicated that overexpression of APEX1 negated the action of vitexin against endothelial inflammation, and that endothelial-specific deletion of APEX1 ameliorated atherogenesis. We thus propose targeting APEX1 with vitexin as a potential therapeutic strategy to alleviate atherosclerosis.

The association of cardiometabolic multimorbidity and fear of falling among older adults: Data from the national health and aging trends study.

OBJECTIVES: Cardiometabolic diseases (CMDs) have been individually associated with fall-related outcomes, but their combined effect on fear of falling (FOF) has not been investigated. This study aims to examine the association between cardiometabolic multimorbidity and FOF in older adults. METHODS: Data from the National Health and Aging Trends Study, 4,295 community-dwelling older adults ≥ 65 years were analyzed in this longitudinal study. CMDs were assessed at baseline, including heart disease, diabetes, stroke, and hypertension. FOF was evaluated by asking participants if they worried about falling in the past month. Data were analyzed using multi-adjusted logistic regression. RESULTS: Cardiometabolic multimorbidity was associated with a higher risk of FOF. The combination of heart disease and diabetes showed the highest risk of FOF (OR = 3.47, 95 % CI: 1.63-7.40). CONCLUSIONS: These findings underscore the need for targeted interventions to mitigate the combined impact of cardiometabolic multimorbidity on FOF in older adults.

Gain-of-Function Mutations: An Emerging Advantage for Cancer Biology.

Advances in next-generation sequencing have identified thousands of genomic variants that perturb the normal functions of proteins, further contributing to diverse phenotypic consequences in cancer. Elucidating the functional pathways altered by loss-of-function (LOF) or gain-of-function (GOF) mutations will be crucial for prioritizing cancer-causing variants and their resultant therapeutic liabilities. In this review, we highlight the fundamental function of GOF mutations and discuss the potential mechanistic effects in the context of signaling networks. We also summarize advances in experimental and computational resources, which will dramatically help with studies on the functional and phenotypic consequences of mutations. Together, systematic investigations of the function of GOF mutations will provide an important missing piece for cancer biology and precision therapy.

Pairing-Dependent Plasticity in a Dissected Fly Brain Is Input-Specific and Requires Synaptic CaMKII Enrichment and Nighttime Sleep.

In Drosophila, in vivo functional imaging studies revealed that associative memory formation is coupled to a cascade of neural plasticity events in distinct compartments of the mushroom body (MB). In-depth investigation of the circuit dynamics, however, will require an ex vivo model that faithfully mirrors these events to allow direct manipulations of circuit elements that are inaccessible in the intact fly. The current ex vivo models have been able to reproduce the fundamental plasticity of aversive short-term memory, a potentiation of the MB intrinsic neuron (Kenyon cells [KCs]) responses after artificial learning ex vivo However, this potentiation showed different localization and encoding properties from those reported in vivo and failed to generate the previously reported suppression plasticity in the MB output neurons (MBONs). Here, we develop an ex vivo model using the female Drosophila brain that recapitulates behaviorally evoked plasticity in the KCs and MBONs. We demonstrate that this plasticity accurately localizes to the MB α'3 compartment and is encoded by a coincidence between KC activation and dopaminergic input. The formed plasticity is input-specific, requiring pairing of the conditioned stimulus and unconditioned stimulus pathways; hence, we name it pairing-dependent plasticity. Pairing-dependent plasticity formation requires an intact CaMKII gene and is blocked by previous-night sleep deprivation but is rescued by rebound sleep. In conclusion, we show that our ex vivo preparation recapitulates behavioral and imaging results from intact animals and can provide new insights into mechanisms of memory formation at the level of molecules, circuits, and brain state.SIGNIFICANCE STATEMENT The mammalian ex vivo LTP model enabled in-depth investigation of the hippocampal memory circuit. We develop a parallel model to study the Drosophila mushroom body (MB) memory circuit. Pairing activation of the conditioned stimulus and unconditioned stimulus pathways in dissected brains induces a potentiation pairing-dependent plasticity (PDP) in the axons of α'ß' Kenyon cells and a suppression PDP in the dendrites of their postsynaptic MB output neurons, localized in the MB α'3 compartment. This PDP is input-specific and requires the 3' untranslated region of CaMKII Interestingly, ex vivo PDP carries information about the animal's experience before dissection; brains from sleep-deprived animals fail to form PDP, whereas those from animals who recovered 2 h of their lost sleep form PDP.

Aging-associated REGγ proteasome decline predisposes to tauopathy.

The REGγ-20S proteasome is an ubiquitin- and ATP-independent degradation system, targeting selective substrates, possibly helping to regulate aging. The studies we report here demonstrate that aging-associated REGγ decline predisposes to decreasing tau turnover, as in a tauopathy. The REGγ proteasome promotes degradation of human and mouse tau, notably phosphorylated tau and toxic tau oligomers that shuttle between the cytoplasm and nuclei. REGγ-mediated proteasomal degradation of tau was validated in 3- to 12-month-old REGγ KO mice, REGγ KO;PS19 mice, and PS19 mice with forebrain conditional neuron-specific overexpression of REGγ (REGγ OE) and behavioral abnormalities. Coupled with tau accumulation, we found with REGγ-deficiency, neuron loss, dendrite reduction, tau filament accumulation, and microglial activation are much more prominent in the REGγ KO;PS19 than the PS19 model. Moreover, we observed that the degenerative neuronal lesions and aberrant behaviors were alleviated in REGγ OE;PS19 mice. Memory and other behavior analysis substantiate the role of REGγ in prevention of tauopathy-like symptoms. In addition, we investigated the potential mechanism underlying aging-related REGγ decline. This study provides valuable insights into the novel regulatory mechanisms and potential therapeutic targets for tau-related neurodegenerative diseases.

Reconstructing the immunosenescence core pathway reveals global characteristics in pan-cancer.

Immunosenescence has been demonstrated to play an important role in tumor progression. However, there is lacking comprehensive analyses of immunosenescence-related pathways. Meanwhile, the sex disparities of immunosenescence in cancer are still poorly understood. In this study, we analyzed the multi-omics data of 12,836 tumor samples, including genomics, transcriptomics, epigenomics, proteomics, and metabolomics. We systematically identified immunosenescence pathways that were disordered across cancer types. The mutations and copy number variations of immunosenescence pathways were found to be more active in pan-cancer. We reconstructed the immunosenescence core pathways (ISC-pathways) to improve the ability of prognostic stratification in 33 cancer types. We also found the head and neck squamous carcinoma (HNSC) contained abundant sex-specific immunosenescence features and showed sex differences in survival. We found that OSI-027 was a potential sex-specific drug in HNSC tumors, which tended to be more effective in male HNSC by targeting the MTOR gene in the PI3K-Akt signaling pathway. In conclusion, our study provided a systematic understanding of immunosenescence pathways and revealed the global characteristics of immunosenescence in pan-cancer. We highlighted MTOR gene could be a powerful immunosenescence biomarker of HNSC that helps to develop sex-specific immunosenescence drugs.

CiTSA: a comprehensive platform provides experimentally supported signatures of cancer immunotherapy and analysis tools based on bulk and scRNA-seq data.

Immunotherapy has greatly changed the status of cancer treatment, and many patients do not respond or develop acquired resistance. The related research is blocked by lacking of comprehensive resources for researchers to discovery and analysis signatures, then further exploring the mechanisms. Here, we first offered a benchmarking dataset of experimentally supported signatures of cancer immunotherapy by manually curated from published literature works and provided an overview. We then developed CiTSA ( http://bio-bigdata.hrbmu.edu.cn/CiTSA/ ) which stores 878 entries of experimentally supported associations between 412 signatures such as genes, cells, and immunotherapy across 30 cancer types. CiTSA also provides flexible online tools to identify and visualize molecular/cell feature and interaction, to perform function, correlation, and survival analysis, and to execute cell clustering, cluster activity, and cell-cell communication analysis based on single cell and bulk datasets of cancer immunotherapy. In summary, we provided an overview of experimentally supported cancer immunotherapy signatures and developed CiTSA which is a comprehensive and high-quality resource and is helpful for understanding the mechanism of cancer immunity and immunotherapy, developing novel therapeutic targets and promoting precision immunotherapy for cancer.

Microbial production of trans-aconitic acid.

Trans-aconitic acid (TAA) is a promising bio-based chemical with the structure of unsaturated tricarboxylic acid, and also has the potential to be a non-toxic nematicide as a potent inhibitor of aconitase. However, TAA has not been commercialized because the traditional production processes of plant extraction and chemical synthesis cannot achieve large-scale production at a low cost. The availability of TAA is a serious obstacle to its widespread application. In this study, we developed an efficient microbial synthesis and fermentation production process for TAA. An engineered Aspergillus terreus strain producing cis-aconitic acid and TAA was constructed by blocking itaconic acid biosynthesis in the industrial itaconic acid-producing strain. Through heterologous expression of exogenous aconitate isomerase, we further designed a more efficient cell factory to specifically produce TAA. Subsequently, the fermentation process was developed and scaled up step-by-step, achieving a TAA titer of 60 g L-1 at the demonstration scale of a 20 m3 fermenter. Finally, the field evaluation of the produced TAA for control of the root-knot nematodes was performed in a field trial, effectively reducing the damage of the root-knot nematode. Our work provides a commercially viable solution for the green manufacturing of TAA, which will significantly facilitate biopesticide development and promote its widespread application as a bio-based chemical.