Opioid-induced fragile-like regulatory T cells contribute to withdrawal.

Dysregulation of the immune system is a cardinal feature of opioid addiction. Here, we characterize the landscape of peripheral immune cells from patients with opioid use disorder and from healthy controls. Opioid-associated blood exhibited an abnormal distribution of immune cells characterized by a significant expansion of fragile-like regulatory T cells (Tregs), which was positively correlated with the withdrawal score. Analogously, opioid-treated mice also showed enhanced Treg-derived interferon-γ (IFN-γ) expression. IFN-γ signaling reshaped synaptic morphology in nucleus accumbens (NAc) neurons, modulating subsequent withdrawal symptoms. We demonstrate that opioids increase the expression of neuron-derived C-C motif chemokine ligand 2 (Ccl2) and disrupted blood-brain barrier (BBB) integrity through the downregulation of astrocyte-derived fatty-acid-binding protein 7 (Fabp7), which both triggered peripheral Treg infiltration into NAc. Our study demonstrates that opioids drive the expansion of fragile-like Tregs and favor peripheral Treg diapedesis across the BBB, which leads to IFN-γ-mediated synaptic instability and subsequent withdrawal symptoms.

Bat ASC2 suppresses inflammasomes and ameliorates inflammatory diseases.

Bats are special in their ability to live long and host many emerging viruses. Our previous studies showed that bats have altered inflammasomes, which are central players in aging and infection. However, the role of inflammasome signaling in combating inflammatory diseases remains poorly understood. Here, we report bat ASC2 as a potent negative regulator of inflammasomes. Bat ASC2 is highly expressed at both the mRNA and protein levels and is highly potent in inhibiting human and mouse inflammasomes. Transgenic expression of bat ASC2 in mice reduced the severity of peritonitis induced by gout crystals and ASC particles. Bat ASC2 also dampened inflammation induced by multiple viruses and reduced mortality of influenza A virus infection. Importantly, it also suppressed SARS-CoV-2-immune-complex-induced inflammasome activation. Four key residues were identified for the gain of function of bat ASC2. Our results demonstrate that bat ASC2 is an important negative regulator of inflammasomes with therapeutic potential in inflammatory diseases.

Single-cell transcriptome analysis of the in vivo response to viral infection in the cave nectar bat Eonycteris spelaea.

Bats are reservoir hosts of many zoonotic viruses with pandemic potential. We utilized single-cell transcriptome sequencing (scRNA-seq) to analyze the immune response in bat lungs upon in vivo infection with a double-stranded RNA virus, Pteropine orthoreovirus PRV3M. Bat neutrophils were distinguished by high basal IDO1 expression. NK cells and T cells were the most abundant immune cells in lung tissue. Three distinct CD8+ effector T cell populations could be delineated by differential expression of KLRB1, GFRA2, and DPP4. Select NK and T clusters increased expression of genes involved in T cell activation and effector function early after viral infection. Alveolar macrophages and classical monocytes drove antiviral interferon signaling. Infection expanded a CSF1R+ population expressing collagen-like genes, which became the predominant myeloid cell type post-infection. This work uncovers features relevant to viral disease tolerance in bats, lays a foundation for future experimental work, and serves as a resource for comparative immunology studies.

Three-dimensional electronic microfliers inspired by wind-dispersed seeds.

Large, distributed collections of miniaturized, wireless electronic devices1,2 may form the basis of future systems for environmental monitoring3, population surveillance4, disease management5 and other applications that demand coverage over expansive spatial scales. Aerial schemes to distribute the components for such networks are required, and-inspired by wind-dispersed seeds6-we examined passive structures designed for controlled, unpowered flight across natural environments or city settings. Techniques in mechanically guided assembly of three-dimensional (3D) mesostructures7-9 provide access to miniature, 3D fliers optimized for such purposes, in processes that align with the most sophisticated production techniques for electronic, optoelectronic, microfluidic and microelectromechanical technologies. Here we demonstrate a range of 3D macro-, meso- and microscale fliers produced in this manner, including those that incorporate active electronic and colorimetric payloads. Analytical, computational and experimental studies of the aerodynamics of high-performance structures of this type establish a set of fundamental considerations in bio-inspired design, with a focus on 3D fliers that exhibit controlled rotational kinematics and low terminal velocities. An approach that represents these complex 3D structures as discrete numbers of blades captures the essential physics in simple, analytical scaling forms, validated by computational and experimental results. Battery-free, wireless devices and colorimetric sensors for environmental measurements provide simple examples of a wide spectrum of applications of these unusual concepts.

DDID: a comprehensive resource for visualization and analysis of diet-drug interactions.

Diet-drug interactions (DDIs) are pivotal in drug discovery and pharmacovigilance. DDIs can modify the systemic bioavailability/pharmacokinetics of drugs, posing a threat to public health and patient safety. Therefore, it is crucial to establish a platform to reveal the correlation between diets and drugs. Accordingly, we have established a publicly accessible online platform, known as Diet-Drug Interactions Database (DDID, https://bddg.hznu.edu.cn/ddid/), to systematically detail the correlation and corresponding mechanisms of DDIs. The platform comprises 1338 foods/herbs, encompassing flora and fauna, alongside 1516 widely used drugs and 23 950 interaction records. All interactions are meticulously scrutinized and segmented into five categories, thereby resulting in evaluations (positive, negative, no effect, harmful and possible). Besides, cross-linkages between foods/herbs, drugs and other databases are furnished. In conclusion, DDID is a useful resource for comprehending the correlation between foods, herbs and drugs and holds a promise to enhance drug utilization and research on drug combinations.

FERREG: ferroptosis-based regulation of disease occurrence, progression and therapeutic response.

Ferroptosis is a non-apoptotic, iron-dependent regulatory form of cell death characterized by the accumulation of intracellular reactive oxygen species. In recent years, a large and growing body of literature has investigated ferroptosis. Since ferroptosis is associated with various physiological activities and regulated by a variety of cellular metabolism and mitochondrial activity, ferroptosis has been closely related to the occurrence and development of many diseases, including cancer, aging, neurodegenerative diseases, ischemia-reperfusion injury and other pathological cell death. The regulation of ferroptosis mainly focuses on three pathways: system Xc-/GPX4 axis, lipid peroxidation and iron metabolism. The genes involved in these processes were divided into driver, suppressor and marker. Importantly, small molecules or drugs that mediate the expression of these genes are often good treatments in the clinic. Herein, a newly developed database, named 'FERREG', is documented to (i) providing the data of ferroptosis-related regulation of diseases occurrence, progression and drug response; (ii) explicitly describing the molecular mechanisms underlying each regulation; and (iii) fully referencing the collected data by cross-linking them to available databases. Collectively, FERREG contains 51 targets, 718 regulators, 445 ferroptosis-related drugs and 158 ferroptosis-related disease responses. FERREG can be accessed at https://idrblab.org/ferreg/.

MoDAFold: a strategy for predicting the structure of missense mutant protein based on AlphaFold2 and molecular dynamics.

Protein structure prediction is a longstanding issue crucial for identifying new drug targets and providing a mechanistic understanding of protein functions. To enhance the progress in this field, a spectrum of computational methodologies has been cultivated. AlphaFold2 has exhibited exceptional precision in predicting wild-type protein structures, with performance exceeding that of other methods. However, predicting the structures of missense mutant proteins using AlphaFold2 remains challenging due to the intricate and substantial structural alterations caused by minor sequence variations in the mutant proteins. Molecular dynamics (MD) has been validated for precisely capturing changes in amino acid interactions attributed to protein mutations. Therefore, for the first time, a strategy entitled 'MoDAFold' was proposed to improve the accuracy and reliability of missense mutant protein structure prediction by combining AlphaFold2 with MD. Multiple case studies have confirmed the superior performance of MoDAFold compared to other methods, particularly AlphaFold2.

CovEpiAb: a comprehensive database and analysis resource for immune epitopes and antibodies of human coronaviruses.

Coronaviruses have threatened humans repeatedly, especially COVID-19 caused by SARS-CoV-2, which has posed a substantial threat to global public health. SARS-CoV-2 continuously evolves through random mutation, resulting in a significant decrease in the efficacy of existing vaccines and neutralizing antibody drugs. It is critical to assess immune escape caused by viral mutations and develop broad-spectrum vaccines and neutralizing antibodies targeting conserved epitopes. Thus, we constructed CovEpiAb, a comprehensive database and analysis resource of human coronavirus (HCoVs) immune epitopes and antibodies. CovEpiAb contains information on over 60 000 experimentally validated epitopes and over 12 000 antibodies for HCoVs and SARS-CoV-2 variants. The database is unique in (1) classifying and annotating cross-reactive epitopes from different viruses and variants; (2) providing molecular and experimental interaction profiles of antibodies, including structure-based binding sites and around 70 000 data on binding affinity and neutralizing activity; (3) providing virological characteristics of current and past circulating SARS-CoV-2 variants and in vitro activity of various therapeutics; and (4) offering site-level annotations of key functional features, including antibody binding, immunological epitopes, SARS-CoV-2 mutations and conservation across HCoVs. In addition, we developed an integrated pipeline for epitope prediction named COVEP, which is available from the webpage of CovEpiAb. CovEpiAb is freely accessible at https://pgx.zju.edu.cn/covepiab/.

Hello darkness, my old friend: 3-KETOACYL-COENZYME A SYNTHASE4 is a branch point in the regulation of triacylglycerol synthesis in Arabidopsis thaliana.

Plant lipids are important as alternative sources of carbon and energy when sugars or starch are limited. Here, we applied combined heat and darkness or extended darkness to a panel of ∼300 Arabidopsis (Arabidopsis thaliana) accessions to study lipid remodeling under carbon starvation. Natural allelic variation at 3-KETOACYL-COENZYME A SYNTHASE4 (KCS4), a gene encoding an enzyme involved in very long chain fatty acid (VLCFA) synthesis, underlies the differential accumulation of polyunsaturated triacylglycerols (puTAGs) under stress. Ectopic expression of KCS4 in yeast and plants proved that KCS4 is a functional enzyme localized in the endoplasmic reticulum with specificity for C22 and C24 saturated acyl-CoA. Allelic mutants and transient overexpression in planta revealed the differential role of KCS4 alleles in VLCFA synthesis and leaf wax coverage, puTAG accumulation, and biomass. Moreover, the region harboring KCS4 is under high selective pressure and allelic variation at KCS4 correlates with environmental parameters from the locales of Arabidopsis accessions. Our results provide evidence that KCS4 plays a decisive role in the subsequent fate of fatty acids released from chloroplast membrane lipids under carbon starvation. This work sheds light on both plant response mechanisms and the evolutionary events shaping the lipidome under carbon starvation.

The osmotic stress-activated receptor-like kinase DPY1 mediates SnRK2 kinase activation and drought tolerance in Setaria.

Plant genomes encode many receptor-like kinases (RLKs) that localize to the cell surface and perceive a wide variety of environmental cues to initiate downstream signaling cascades. Whether these RLKs participate in dehydration stress signaling in plants is largely unknown. DROOPY LEAF1 (DPY1), a leucine-rich repeat (LRR)-RLK, was recently shown to regulate plant architecture by orchestrating early brassinosteroid signaling in foxtail millet (Setaria italica). Here, we show that DPY1 is essential for the acclimation of foxtail millet to drought stress. DPY1 can be phosphorylated and activated in response to osmotic stress and is required for more than half of osmotic stress-induced global phosphorylation events, including the phosphorylation of sucrose nonfermenting kinase 2s (SnRK2s), the central kinases involved in osmotic stress. DPY1 acts upstream of STRESS-ACTIVATED PROTEIN KINASE 6 (SAPK6, a subclass I SnRK2) and is required for full SAPK6 activation, thereby allowing regulation of downstream genes to mount a response against drought stress. These signaling events are largely independent of DPY1-mediated brassinosteroid signaling. The DPY1-SAPK6 module is specific to seed plants and is absent in ancestral nonseed plants. Our findings reveal a dehydration stress-activated RLK that plays an indispensable role in osmotic stress signaling and mediates SnRK2 activation at the cell surface.

A genomic and epigenomic atlas of prostate cancer in Asian populations.

Prostate cancer is the second most common cancer in men worldwide1. Over the past decade, large-scale integrative genomics efforts have enhanced our understanding of this disease by characterizing its genetic and epigenetic landscape in thousands of patients2,3. However, most tumours profiled in these studies were obtained from patients from Western populations. Here we produced and analysed whole-genome, whole-transcriptome and DNA methylation data for 208 pairs of tumour tissue samples and matched healthy control tissue from Chinese patients with primary prostate cancer. Systematic comparison with published data from 2,554 prostate tumours revealed that the genomic alteration signatures in Chinese patients were markedly distinct from those of Western cohorts: specifically, 41% of tumours contained mutations in FOXA1 and 18% each had deletions in ZNF292 and CHD1. Alterations of the genome and epigenome were correlated and were predictive of disease phenotype and progression. Coding and noncoding mutations, as well as epimutations, converged on pathways that are important for prostate cancer, providing insights into this devastating disease. These discoveries underscore the importance of including population context in constructing comprehensive genomic maps for disease.

SingPro: a knowledge base providing single-cell proteomic data.

Single-cell proteomics (SCP) has emerged as a powerful tool for detecting cellular heterogeneity, offering unprecedented insights into biological mechanisms that are masked in bulk cell populations. With the rapid advancements in AI-based time trajectory analysis and cell subpopulation identification, there exists a pressing need for a database that not only provides SCP raw data but also explicitly describes experimental details and protein expression profiles. However, no such database has been available yet. In this study, a database, entitled 'SingPro', specializing in single-cell proteomics was thus developed. It was unique in (a) systematically providing the SCP raw data for both mass spectrometry-based and flow cytometry-based studies and (b) explicitly describing experimental detail for SCP study and expression profile of any studied protein. Anticipating a robust interest from the research community, this database is poised to become an invaluable repository for OMICs-based biomedical studies. Access to SingPro is unrestricted and does not mandate a login at: http://idrblab.org/singpro/.

PROSCA: an online platform for humanized scaffold mining facilitating rational protein engineering.

Protein scaffolds with small size, high stability and low immunogenicity show important applications in the field of protein engineering and design. However, no relevant computational platform has been reported yet to mining such scaffolds with the desired properties from massive protein structures in human body. Here, we developed PROSCA, a structure-based online platform dedicated to explore the space of the entire human proteome, and to discovery new privileged protein scaffolds with potential engineering value that have never been noticed. PROSCA accepts structure of protein as an input, which can be subsequently aligned with a certain class of protein structures (e.g. the human proteome either from experientially resolved or AlphaFold2 predicted structures, and the human proteins belonging to specific families or domains), and outputs humanized protein scaffolds which are structurally similar with the input protein as well as other related important information such as families, sequences, structures and expression level in human tissues. Through PROSCA, the user can also get excellent experience in visualizations of protein structures and expression overviews, and download the figures and tables of results which can be customized according to the user's needs. Along with the advanced protein engineering and selection technologies, PROSCA will facilitate the rational design of new functional proteins with privileged scaffolds. PROSCA is freely available at https://idrblab.org/prosca/.

INTEDE 2.0: the metabolic roadmap of drugs.

The metabolic roadmap of drugs (MRD) is a comprehensive atlas for understanding the stepwise and sequential metabolism of certain drug in living organisms. It plays a vital role in lead optimization, personalized medication, and ADMET research. The MRD consists of three main components: (i) the sequential catalyses of drug and its metabolites by different drug-metabolizing enzymes (DMEs), (ii) a comprehensive collection of metabolic reactions along the entire MRD and (iii) a systematic description on efficacy & toxicity for all metabolites of a studied drug. However, there is no database available for describing the comprehensive metabolic roadmaps of drugs. Therefore, in this study, a major update of INTEDE was conducted, which provided the stepwise & sequential metabolic roadmaps for a total of 4701 drugs, and a total of 22 165 metabolic reactions containing 1088 DMEs and 18 882 drug metabolites. Additionally, the INTEDE 2.0 labeled the pharmacological properties (pharmacological activity or toxicity) of metabolites and provided their structural information. Furthermore, 3717 drug metabolism relationships were supplemented (from 7338 to 11 055). All in all, INTEDE 2.0 is highly expected to attract broad interests from related research community and serve as an essential supplement to existing pharmaceutical/biological/chemical databases. INTEDE 2.0 can now be accessible freely without any login requirement at: http://idrblab.org/intede/.

VARIDT 3.0: the phenotypic and regulatory variability of drug transporter.

The phenotypic and regulatory variability of drug transporter (DT) are vital for the understanding of drug responses, drug-drug interactions, multidrug resistances, and so on. The ADME property of a drug is collectively determined by multiple types of variability, such as: microbiota influence (MBI), transcriptional regulation (TSR), epigenetics regulation (EGR), exogenous modulation (EGM) and post-translational modification (PTM). However, no database has yet been available to comprehensively describe these valuable variabilities of DTs. In this study, a major update of VARIDT was therefore conducted, which gave 2072 MBIs, 10 610 TSRs, 46 748 EGRs, 12 209 EGMs and 10 255 PTMs. These variability data were closely related to the transportation of 585 approved and 301 clinical trial drugs for treating 572 diseases. Moreover, the majority of the DTs in this database were found with multiple variabilities, which allowed a collective consideration in determining the ADME properties of a drug. All in all, VARIDT 3.0 is expected to be a popular data repository that could become an essential complement to existing pharmaceutical databases, and is freely accessible without any login requirement at: https://idrblab.org/varidt/.

CellSTAR: a comprehensive resource for single-cell transcriptomic annotation.

Large-scale studies of single-cell sequencing and biological experiments have successfully revealed expression patterns that distinguish different cell types in tissues, emphasizing the importance of studying cellular heterogeneity and accurately annotating cell types. Analysis of gene expression profiles in these experiments provides two essential types of data for cell type annotation: annotated references and canonical markers. In this study, the first comprehensive database of single-cell transcriptomic annotation resource (CellSTAR) was thus developed. It is unique in (a) offering the comprehensive expertly annotated reference data for annotating hundreds of cell types for the first time and (b) enabling the collective consideration of reference data and marker genes by incorporating tens of thousands of markers. Given its unique features, CellSTAR is expected to attract broad research interests from the technological innovations in single-cell transcriptomics, the studies of cellular heterogeneity & dynamics, and so on. It is now publicly accessible without any login requirement at: https://idrblab.org/cellstar.

TTD: Therapeutic Target Database describing target druggability information.

Target discovery is one of the essential steps in modern drug development, and the identification of promising targets is fundamental for developing first-in-class drug. A variety of methods have emerged for target assessment based on druggability analysis, which refers to the likelihood of a target being effectively modulated by drug-like agents. In the therapeutic target database (TTD), nine categories of established druggability characteristics were thus collected for 426 successful, 1014 clinical trial, 212 preclinical/patented, and 1479 literature-reported targets via systematic review. These characteristic categories were classified into three distinct perspectives: molecular interaction/regulation, human system profile and cell-based expression variation. With the rapid progression of technology and concerted effort in drug discovery, TTD and other databases were highly expected to facilitate the explorations of druggability characteristics for the discovery and validation of innovative drug target. TTD is now freely accessible at: https://idrblab.org/ttd/.

ADCdb: the database of antibody-drug conjugates.

Antibody-drug conjugates (ADCs) are a class of innovative biopharmaceutical drugs, which, via their antibody (mAb) component, deliver and release their potent warhead (a.k.a. payload) at the disease site, thereby simultaneously improving the efficacy of delivered therapy and reducing its off-target toxicity. To design ADCs of promising efficacy, it is crucial to have the critical data of pharma-information and biological activities for each ADC. However, no such database has been constructed yet. In this study, a database named ADCdb focusing on providing ADC information (especially its pharma-information and biological activities) from multiple perspectives was thus developed. Particularly, a total of 6572 ADCs (359 approved by FDA or in clinical trial pipeline, 501 in preclinical test, 819 with in-vivo testing data, 1868 with cell line/target testing data, 3025 without in-vivo/cell line/target testing data) together with their explicit pharma-information was collected and provided. Moreover, a total of 9171 literature-reported activities were discovered, which were identified from diverse clinical trial pipelines, model organisms, patient/cell-derived xenograft models, etc. Due to the significance of ADCs and their relevant data, this new database was expected to attract broad interests from diverse research fields of current biopharmaceutical drug discovery. The ADCdb is now publicly accessible at: https://idrblab.org/adcdb/.

TheMarker: a comprehensive database of therapeutic biomarkers.

Distinct from the traditional diagnostic/prognostic biomarker (adopted as the indicator of disease state/process), the therapeutic biomarker (ThMAR) has emerged to be very crucial in the clinical development and clinical practice of all therapies. There are five types of ThMAR that have been found to play indispensable roles in various stages of drug discovery, such as: Pharmacodynamic Biomarker essential for guaranteeing the pharmacological effects of a therapy, Safety Biomarker critical for assessing the extent or likelihood of therapy-induced toxicity, Monitoring Biomarker indispensable for guiding clinical management by serially measuring patients' status, Predictive Biomarker crucial for maximizing the clinical outcome of a therapy for specific individuals, and Surrogate Endpoint fundamental for accelerating the approval of a therapy. However, these data of ThMARs has not been comprehensively described by any of the existing databases. Herein, a database, named 'TheMarker', was therefore constructed to (a) systematically offer all five types of ThMAR used at different stages of drug development, (b) comprehensively describe ThMAR information for the largest number of drugs among available databases, (c) extensively cover the widest disease classes by not just focusing on anticancer therapies. These data in TheMarker are expected to have great implication and significant impact on drug discovery and clinical practice, and it is freely accessible without any login requirement at: https://idrblab.org/themarker.

Investing in mini-livestock production for food security and carbon neutrality in China.

Future food farming technology faces challenges that must integrate the core goal of keeping the global temperature increase within 1.5 °C without reducing food security and nutrition. Here, we show that boosting the production of insects and earthworms based on food waste and livestock manure to provide food and feed in China will greatly contribute to meeting the country's food security and carbon neutrality pledges. By substituting domestic products with mini-livestock (defined as earthworms and insects produced for food or feed) protein and utilizing the recovered land for bioenergy production plus carbon capture and storage, China's agricultural sector could become carbon-neutral and reduce feed protein imports to near zero. This structural change may lead to reducing greenhouse gas emissions by 2,350 Tg CO2eq per year globally when both domestic and imported products are substituted. Overall, the success of mini-livestock protein production in achieving carbon neutrality and food security for China and its major trading partners depends on how the substitution strategies will be implemented and how the recovered agricultural land will be managed, e.g., free use for afforestation and bioenergy or by restricting this land to food crop use. Using China as an example, this study also demonstrates the potential of mini-livestock for decreasing the environmental burden of food production in general.