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Alpine lakes, characterized by isolation, low temperatures, oligotrophic conditions, and intense ultraviolet radiation, remain a poorly explored ecosystem for RNA viruses. Here, we present the first comprehensive metatranscriptomic study of RNA viruses in Lake Nam Co, a high-altitude alkaline saline lake on the Tibetan Plateau. Using a combination of sequence- and structure-based homology searches, we identified 742 RNA virus species, including 383 novel genus-level groups and 84 novel family-level groups exclusively found in Lake Nam Co. These findings significantly expand the known diversity of the Orthornavirae , uncovering evolutionary adaptations such as permutated RNA-dependent RNA polymerase motifs and distinct RNA secondary structures. Notably, 14 additional RNA virus families potentially infecting prokaryotes were predicted, broadening the known host range of RNA viruses and questioning the traditional assumption that RNA viruses predominantly target eukaryotes. The presence of auxiliary metabolic genes in viral genomes suggested that RNA viruses (families f . 0102 and Nam-Co_family_51) exploit host energy production mechanisms in energy-limited alpine lakes. Low nucleotide diversity, single nucleotide polymorphism frequencies, and pN/pS ratios indicate strong purifying selection in Nam Co viral populations. Our findings offer insights into RNA virus evolution and ecology, highlighting the importance of extreme environments in uncovering hidden viral diversity and further shed light into their potential ecological implications, particularly in the context of climate change., Competing Interests: Competing interests statement:The authors declare no competing interest.

Cell-cell interactions are essential for the function and contextual regulation of biological tissues. We present a platform for high-throughput microfluidics-supported genetic screening of functional regulators of cell-cell interactions. Systematic perturbation of encapsulated associated cells followed by sequencing (SPEAC-seq) combines genome-wide CRISPR libraries, cell coculture in droplets and microfluidic droplet sorting based on functional read-outs determined by fluorescent reporter circuits to enable the unbiased discovery of interaction regulators. This technique overcomes limitations of traditional methods for characterization of cell-cell communication, which require a priori knowledge of cellular interactions, are highly engineered and lack functional read-outs. As an example of this technique, we describe the investigation of neuroinflammatory intercellular communication between microglia and astrocytes, using genome-wide CRISPR-Cas9 inactivation libraries and fluorescent reporters of NF-κB activation. This approach enabled the discovery of thousands of microglial regulators of astrocyte NF-κB activation important for the control of central nervous system inflammation. Importantly, SPEAC-seq can be adapted to different cell types, screening modalities, cell functions and physiological contexts, only limited by the ability to fluorescently report cell functions and by droplet cultivation conditions. Performing genome-wide screening takes less than 2 weeks and requires microfluidics capabilities. Thus, SPEAC-seq enables the large-scale investigation of cell-cell interactions., Competing Interests: Competing interests: M.A.W., I.C.C. and F.J.Q. have filed a patent on SPEAC-seq. The remaining authors declare no competing interests., (© 2024. Springer Nature Limited.)

This study investigates a novel approach for assessing the health status of rotating machinery transmission systems by analyzing the dynamic degradation of bearings. The proposed method generates multi-dimensional data by creating virtual states and constructs a multi-dimensional model using virtual state-space in conjunction with mechanism model analysis. Innovatively, the Hammerstein-Wiener (HW) modeling technique from control theory is applied to identify these dynamic multi-dimensional models. The modeling experiments are performed, focusing on the model's input and output types, the selection of nonlinear module estimators, the configuration of linear module transfer functions, and condition transfer. Dynamic degradation response signals are generated, and the method is validated using four widely recognized databases consisting of accurate measurement signals collected by vibration sensors. Experimental results demonstrated that the model achieved a modeling accuracy of 99% for multiple bearings under various conditions. The effectiveness of this dynamic modeling method is further confirmed through comparative experimental data and signal images. This approach offers a novel reference for evaluating the health status of transmission systems.

Cancer development and progression are generally associated with gene dysregulation, often resulting from changes in the transcription factor (TF) sequence or expression. Identifying key TFs involved in cancer gene regulation provides a framework for potential new therapeutics. This study presents a large-scale cancer gene TF-DNA interaction network, as well as an extensive promoter clone resource for future studies. Highly connected TFs bind to promoters of genes associated with either good or poor cancer prognosis, suggesting that strategies aimed at shifting gene expression balance between these two prognostic groups may be inherently complex. However, we identified potential for oncogene-targeted therapeutics, with half of the tested oncogenes being potentially repressed by influencing specific activators or bifunctional TFs. Finally, we investigate the role of intrinsically disordered regions within the key cancer-related TF ESR1 in DNA binding and transcriptional activity, and found that these regions can have complex trade-offs in TF function. Altogether, our study broadens our knowledge of the TFs involved in cancer gene regulation and provides a valuable resource for future studies and therapeutics., (© 2024 Lu et al.)

Disease-associated astrocyte subsets contribute to the pathology of neurologic diseases, including multiple sclerosis and experimental autoimmune encephalomyelitis 1-8 (EAE), an experimental model for multiple sclerosis. However, little is known about the stability of these astrocyte subsets and their ability to integrate past stimulation events. Here we report the identification of an epigenetically controlled memory astrocyte subset that exhibits exacerbated pro-inflammatory responses upon rechallenge. Specifically, using a combination of single-cell RNA sequencing, assay for transposase-accessible chromatin with sequencing, chromatin immunoprecipitation with sequencing, focused interrogation of cells by nucleic acid detection and sequencing, and cell-specific in vivo CRISPR-Cas9-based genetic perturbation studies we established that astrocyte memory is controlled by the metabolic enzyme ATP-citrate lyase (ACLY), which produces acetyl coenzyme A (acetyl-CoA) that is used by histone acetyltransferase p300 to control chromatin accessibility. The number of ACLY + p300 + memory astrocytes is increased in acute and chronic EAE models, and their genetic inactivation ameliorated EAE. We also detected the pro-inflammatory memory phenotype in human astrocytes in vitro; single-cell RNA sequencing and immunohistochemistry studies detected increased numbers of ACLY + p300 + astrocytes in chronic multiple sclerosis lesions. In summary, these studies define an epigenetically controlled memory astrocyte subset that promotes CNS pathology in EAE and, potentially, multiple sclerosis. These findings may guide novel therapeutic approaches for multiple sclerosis and other neurologic diseases., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

Protein function annotation has been one of the longstanding issues in biological sciences, and various computational methods have been developed. However, the existing methods suffer from a serious long-tail problem, with a large number of GO families containing few annotated proteins. Herein, an innovative strategy named AnnoPRO was therefore constructed by enabling sequence-based multi-scale protein representation, dual-path protein encoding using pre-training, and function annotation by long short-term memory-based decoding. A variety of case studies based on different benchmarks were conducted, which confirmed the superior performance of AnnoPRO among available methods. Source code and models have been made freely available at: https://github.com/idrblab/AnnoPRO and https://zenodo.org/records/10012272., (© 2024. The Author(s).)

Cancer development and progression are generally associated with dysregulation of gene expression, often resulting from changes in transcription factor (TF) sequence or expression. Identifying key TFs involved in cancer gene regulation provides a framework for potential new therapeutics. This study presents a large-scale cancer gene TF-DNA interaction network as well as an extensive promoter clone resource for future studies. Most highly connected TFs do not show a preference for binding to promoters of genes associated with either good or poor cancer prognosis, suggesting that emerging strategies aimed at shifting gene expression balance between these two prognostic groups may be inherently complex. However, we identified potential for oncogene targeted therapeutics, with half of the tested oncogenes being potentially repressed by influencing specific activator or bifunctional TFs. Finally, we investigate the role of intrinsically disordered regions within the key cancer-related TF estrogen receptor ɑ (ESR1) on DNA binding and transcriptional activity, and found that these regions can have complex trade-offs in TF function. Altogether, our study not only broadens our knowledge of TFs involved in the cancer gene regulatory network but also provides a valuable resource for future studies, laying a foundation for potential therapeutic strategies targeting TFs in cancer., Competing Interests: Conflict of Interest The authors declare no conflicts of interest.

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., (© The Author(s) 2024. Published by Oxford University Press.)

Actinobacillus pleuropneumoniae (APP) is responsible for causing Porcine pleuropneumonia (PCP) in pigs. However, using vaccines and antibiotics to prevent and control this disease has become more difficult due to increased bacterial resistance and weak cross-immunity between different APP types. Naringin (NAR), a dihydroflavonoid found in citrus fruit peels, has been recognized as having significant therapeutic effects on inflammatory diseases of the respiratory system. In this study, we investigated the effects of NAR on the inflammatory response caused by APP through both in vivo and in vitro models. The results showed that NAR reduced the number of neutrophils (NEs) in the bronchoalveolar lavage fluid (BALF), and decreased lung injury and the expression of proteins related to the NLRP3 inflammasome after exposure to APP. In addition, NAR inhibited the nuclear translocation of nuclear factor kappa-B (NF-κB) P65 in porcine alveolar macrophage (PAMs), reduced protein expression of NLRP3 and Caspase-1, and reduced the secretion of pro-inflammatory cytokines induced by APP. Furthermore, NAR prevented the assembly of the NLRP3 inflammasome complex by reducing protein interaction between NLRP3, Caspase-1, and ASC. NAR also inhibited the potassium (K + ) efflux induced by APP. Overall, these findings suggest that NAR can effectively reduce the lung inflammation caused by APP by inhibiting the over-activated NF-κB/NLRP3 signalling pathway, providing a basis for further exploration of NAR as a potential natural product for preventing and treating APP.

Astrocytes play important roles in the central nervous system (CNS) physiology and pathology. Indeed, astrocyte subsets defined by specific transcriptional activation states contribute to the pathology of neurologic diseases, including multiple sclerosis (MS) and its pre-clinical model experimental autoimmune encephalomyelitis (EAE) 1-8 . However, little is known about the stability of these disease-associated astrocyte subsets, their regulation, and whether they integrate past stimulation events to respond to subsequent challenges. Here, we describe the identification of an epigenetically controlled memory astrocyte subset which exhibits exacerbated pro-inflammatory responses upon re-challenge. Specifically, using a combination of single-cell RNA sequencing (scRNA-seq), assay for transposase-accessible chromatin with sequencing (ATAC-seq), chromatin immunoprecipitation with sequencing (ChIP-seq), focused interrogation of cells by nucleic acid detection and sequencing (FIND-seq), and cell-specific in vivo CRISPR/Cas9-based genetic perturbation studies we established that astrocyte memory is controlled by the metabolic enzyme ATP citrate lyase (ACLY), which produces acetyl coenzyme A (acetyl-CoA) used by the histone acetyltransferase p300 to control chromatin accessibility. ACLY + p300 + memory astrocytes are increased in acute and chronic EAE models; the genetic targeting of ACLY + p300 + astrocytes using CRISPR/Cas9 ameliorated EAE. We also detected responses consistent with a pro-inflammatory memory phenotype in human astrocytes in vitro ; scRNA-seq and immunohistochemistry studies detected increased ACLY + p300 + astrocytes in chronic MS lesions. In summary, these studies define an epigenetically controlled memory astrocyte subset that promotes CNS pathology in EAE and, potentially, MS. These findings may guide novel therapeutic approaches for MS and other neurologic diseases.

RNAs play essential roles in diverse physiological and pathological processes by interacting with other molecules (RNA/protein/compound), and various computational methods are available for identifying these interactions. However, the encoding features provided by existing methods are limited and the existing tools does not offer an effective way to integrate the interacting partners. In this study, a task-specific encoding algorithm for RNAs and RNA-associated interactions was therefore developed. This new algorithm was unique in (a) realizing comprehensive RNA feature encoding by introducing a great many of novel features and (b) enabling task-specific integration of interacting partners using convolutional autoencoder-directed feature embedding. Compared with existing methods/tools, this novel algorithm demonstrated superior performances in diverse benchmark testing studies. This algorithm together with its source code could be readily accessed by all user at: https://idrblab.org/corain/ and https://github.com/idrblab/corain/., (© The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Critically ill patients with Corona Virus Disease 2019 (COVID-19) often develop secondary bacterial infections that pose a significant threat to patient life safety, making the development of drugs to prevent bacterial infections in the lungs critical to clinical care. Naringin (NAR) is one of the significant natural flavonoids rich in Pummelo Peel (Hua Ju Hong), with anti-inflammatory, antimicrobial, and antioxidant activities, and is commonly used in treating respiratory tract infectious diseases. In this study, the in vitro and in vivo findings revealed that, after Klebsiella pneumoniae (Kpn) infection, NAR inhibited overactivation of the nuclear factor kappa-B(NF-κB) signaling pathway in alveolar macrophages of mice, reduced neutrophil (NEs) recruitment, and lowered the induced production of proinflammatory markers, such as Interleukin-6(IL-6) and tumor necrosis factor α(TNF-α). Thus, it suppressed excessive immune responses in the lungs, as well as attenuated the induced pulmonary fibrosis and inflammatory infiltrates. These results suggest that NAR has a preventive effect against Kpn in mice. In addition, the study evaluated NAR's potential toxicity, demonstrating that NAR is safe at effective doses. These results suggested that NAR effectively reduces excessive inflammatory damage in the lungs induced by Kpn and enhances the body's ability to clear bacteria. Therefore, NAR may be an effective and safe healthcare drug for preventing and caring for bacterial pneumonia.

Cooperativity and antagonism between transcription factors (TFs) can drastically modify their binding to regulatory DNA elements. While mapping these relationships between TFs is important for understanding their context-specific functions, existing approaches either rely on DNA binding motif predictions, interrogate one TF at a time, or study individual TFs in parallel. Here, we introduce paired yeast one-hybrid (pY1H) assays to detect cooperativity and antagonism across hundreds of TF-pairs at DNA regions of interest. We provide evidence that a wide variety of TFs are subject to modulation by other TFs in a DNA region-specific manner. We also demonstrate that TF-TF relationships are often affected by alternative isoform usage and identify cooperativity and antagonism between human TFs and viral proteins from human papillomaviruses, Epstein-Barr virus, and other viruses. Altogether, pY1H assays provide a broadly applicable framework to study how different functional relationships affect protein occupancy at regulatory DNA regions., (© 2023. Springer Nature Limited.)

Periodontitis is a chronic inflammatory disease that destroys the integrity of tooth-supporting tissue. Periodontitis is listed as a major oral disease by the World Health Organization and is a public-health problem affecting global oral and systemic health. The fourth national oral health epidemiological survey has revealed that periodontitis is one of the most common oral problems in China. With the development of science and medicine, increased attention is being paid to the importance of oral health and its influence on general health. Accordingly, stomatologists are required to master more relevant information on clinical diagnosis and treatment, as well as to pay more attention to the diagnosis and treatment methods of patients with different systemic diseases. This article expounds the diagnosis and treatment strategy of patients with systemic disease periodontitis. We aimed to help stomatologists make more reasonable diagnosis and treatment decisions.

Dendritic cells (DCs) have a role in the development and activation of self-reactive pathogenic T cells 1,2 . Genetic variants that are associated with the function of DCs have been linked to autoimmune disorders 3,4 , and DCs are therefore attractive therapeutic targets for such diseases. However, developing DC-targeted therapies for autoimmunity requires identification of the mechanisms that regulate DC function. Here, using single-cell and bulk transcriptional and metabolic analyses in combination with cell-specific gene perturbation studies, we identify a regulatory loop of negative feedback that operates in DCs to limit immunopathology. Specifically, we find that lactate, produced by activated DCs and other immune cells, boosts the expression of NDUFA4L2 through a mechanism mediated by hypoxia-inducible factor 1α (HIF-1α). NDUFA4L2 limits the production of mitochondrial reactive oxygen species that activate XBP1-driven transcriptional modules in DCs that are involved in the control of pathogenic autoimmune T cells. We also engineer a probiotic that produces lactate and suppresses T cell autoimmunity through the activation of HIF-1α-NDUFA4L2 signalling in DCs. In summary, we identify an immunometabolic pathway that regulates DC function, and develop a synthetic probiotic for its therapeutic activation., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

The role of B cells in anti-tumour immunity is still debated and, accordingly, immunotherapies have focused on targeting T and natural killer cells to inhibit tumour growth 1,2 . Here, using high-throughput flow cytometry as well as bulk and single-cell RNA-sequencing and B-cell-receptor-sequencing analysis of B cells temporally during B16F10 melanoma growth, we identified a subset of B cells that expands specifically in the draining lymph node over time in tumour-bearing mice. The expanding B cell subset expresses the cell surface molecule T cell immunoglobulin and mucin domain 1 (TIM-1, encoded by Havcr1) and a unique transcriptional signature, including multiple co-inhibitory molecules such as PD-1, TIM-3, TIGIT and LAG-3. Although conditional deletion of these co-inhibitory molecules on B cells had little or no effect on tumour burden, selective deletion of Havcr1 in B cells both substantially inhibited tumour growth and enhanced effector T cell responses. Loss of TIM-1 enhanced the type 1 interferon response in B cells, which augmented B cell activation and increased antigen presentation and co-stimulation, resulting in increased expansion of tumour-specific effector T cells. Our results demonstrate that manipulation of TIM-1-expressing B cells enables engagement of the second arm of adaptive immunity to promote anti-tumour immunity and inhibit tumour growth., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

Motivation: With the rapid advances of RNA sequencing and microarray technologies in non-coding RNA (ncRNA) research, functional tools that perform enrichment analysis for ncRNAs are needed. On the one hand, because of the rapidly growing interest in circRNAs, snoRNAs, and piRNAs, it is essential to develop tools for enrichment analysis for these newly emerged ncRNAs. On the other hand, due to the key role of ncRNAs' interacting target in the determination of their function, the interactions between ncRNA and its corresponding target should be fully considered in functional enrichment. Based on the ncRNA-mRNA/protein-function strategy, some tools have been developed to functionally analyze a single type of ncRNA (the majority focuses on miRNA); in addition, some tools adopt predicted target data and lead to only low-confidence results., Results: Herein, an online tool named RNAenrich was developed to enable the comprehensive and accurate enrichment analysis of ncRNAs. It is unique in (i) realizing the enrichment analysis for various RNA types in humans and mice, such as miRNA, lncRNA, circRNA, snoRNA, piRNA, and mRNA; (ii) extending the analysis by introducing millions of experimentally validated data of RNA-target interactions as a built-in database; and (iii) providing a comprehensive interacting network among various ncRNAs and targets to facilitate the mechanistic study of ncRNA function. Importantly, RNAenrich led to a more comprehensive and accurate enrichment analysis in a COVID-19-related miRNA case, which was largely attributed to its coverage of comprehensive ncRNA-target interactions., Availability and Implementation: RNAenrich is now freely accessible at https://idrblab.org/rnaenr/., (© The Author(s) 2023. Published by Oxford University Press.)

Dendritic cells (DCs) control the generation of self-reactive pathogenic T cells. Thus, DCs are considered attractive therapeutic targets for autoimmune diseases. Using single-cell and bulk transcriptional and metabolic analyses in combination with cell-specific gene perturbation studies we identified a negative feedback regulatory pathway that operates in DCs to limit immunopathology. Specifically, we found that lactate, produced by activated DCs and other immune cells, boosts NDUFA4L2 expression through a mechanism mediated by HIF-1α. NDUFA4L2 limits the production of mitochondrial reactive oxygen species that activate XBP1-driven transcriptional modules in DCs involved in the control of pathogenic autoimmune T cells. Moreover, we engineered a probiotic that produces lactate and suppresses T-cell autoimmunity in the central nervous system via the activation of HIF-1α/NDUFA4L2 signaling in DCs. In summary, we identified an immunometabolic pathway that regulates DC function, and developed a synthetic probiotic for its therapeutic activation.

Cell-cell interactions in the central nervous system play important roles in neurologic diseases. However, little is known about the specific molecular pathways involved, and methods for their systematic identification are limited. Here, we developed a forward genetic screening platform that combines CRISPR-Cas9 perturbations, cell coculture in picoliter droplets, and microfluidic-based fluorescence-activated droplet sorting to identify mechanisms of cell-cell communication. We used SPEAC-seq (systematic perturbation of encapsulated associated cells followed by sequencing), in combination with in vivo genetic perturbations, to identify microglia-produced amphiregulin as a suppressor of disease-promoting astrocyte responses in multiple sclerosis preclinical models and clinical samples. Thus, SPEAC-seq enables the high-throughput systematic identification of cell-cell communication mechanisms.

Multiple sclerosis is a chronic inflammatory disease of the central nervous system 1 . Astrocytes are heterogeneous glial cells that are resident in the central nervous system and participate in the pathogenesis of multiple sclerosis and its model experimental autoimmune encephalomyelitis 2,3 . However, few unique surface markers are available for the isolation of astrocyte subsets, preventing their analysis and the identification of candidate therapeutic targets; these limitations are further amplified by the rarity of pathogenic astrocytes. Here, to address these challenges, we developed focused interrogation of cells by nucleic acid detection and sequencing (FIND-seq), a high-throughput microfluidic cytometry method that combines encapsulation of cells in droplets, PCR-based detection of target nucleic acids and droplet sorting to enable in-depth transcriptomic analyses of cells of interest at single-cell resolution. We applied FIND-seq to study the regulation of astrocytes characterized by the splicing-driven activation of the transcription factor XBP1, which promotes disease pathology in multiple sclerosis and experimental autoimmune encephalomyelitis 4 . Using FIND-seq in combination with conditional-knockout mice, in vivo CRISPR-Cas9-driven genetic perturbation studies and bulk and single-cell RNA sequencing analyses of samples from mouse experimental autoimmune encephalomyelitis and humans with multiple sclerosis, we identified a new role for the nuclear receptor NR3C2 and its corepressor NCOR2 in limiting XBP1-driven pathogenic astrocyte responses. In summary, we used FIND-seq to identify a therapeutically targetable mechanism that limits XBP1-driven pathogenic astrocyte responses. FIND-seq enables the investigation of previously inaccessible cells, including rare cell subsets defined by unique gene expression signatures or other nucleic acid markers., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

The efficacy and safety of drugs are widely known to be determined by their interactions with multiple molecules of pharmacological importance, and it is therefore essential to systematically depict the molecular atlas and pharma-information of studied drugs. However, our understanding of such information is neither comprehensive nor precise, which necessitates the construction of a new database providing a network containing a large number of drugs and their interacting molecules. Here, a new database describing the molecular atlas and pharma-information of drugs (DrugMAP) was therefore constructed. It provides a comprehensive list of interacting molecules for >30 000 drugs/drug candidates, gives the differential expression patterns for >5000 interacting molecules among different disease sites, ADME (absorption, distribution, metabolism and excretion)-relevant organs and physiological tissues, and weaves a comprehensive and precise network containing >200 000 interactions among drugs and molecules. With the great efforts made to clarify the complex mechanism underlying drug pharmacokinetics and pharmacodynamics and rapidly emerging interests in artificial intelligence (AI)-based network analyses, DrugMAP is expected to become an indispensable supplement to existing databases to facilitate drug discovery. It is now fully and freely accessible at: https://idrblab.org/drugmap/., (© The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Background: Parenteral anti-CD3 Mab (OKT3) has been used to treat transplant rejection and parental administration of a humanized anti-CD3 Mab (Teplizumab) showed positive effects in diabetes. Nasal administration of anti-CD3 Mab has not been carried out in humans. Nasal anti-CD3 Mab suppresses autoimmune diseases and central nervous system (CNS) inflammation in animal models. We investigated the safety and immune effects of a fully humanized, previously uncharacterized nasal anti-CD3 Mab (Foralumab) in humans and its in vitro stimulatory properties., Methods: In vitro , Foralumab were compared to UCHT1 anti-human CD3 mAb. For human administration, 27 healthy volunteers (9 per group) received nasal Foralumab or placebo at a dose of 10ug, 50ug, or 250ug daily for 5 days. Safety was assessed and immune parameters measured on day 1 (pre-treatment), 7, 14, and 30 by FACS and by scRNAseq., Results: In vitro , Foralumab preferentially induced CD8+ T cell stimulation, reduced CD4+ T cell proliferation and lowered expression of IFNg, IL-17 and TNFa. Foralumab induced LAP, TIGIT, and KLRG1 immune checkpoint molecules on CD8+ and CD4+ T cells in a mechanism independent of CD8 T cells. In vivo , nasal Foralumab did not modulate CD3 from the T cell surface at any dose. Immune effects were primarily observed at the 50ug dose and consisted of reduction of CD8+ effector memory cells, an increase in naive CD8+ and CD4+ T cells, and reduced CD8+ T cell granzyme B and perforin expression. Differentially expressed genes observed by scRNAseq in CD8+ and CD4+ populations promoted survival and were anti-inflammatory. In the CD8+ TEMRA population there was induction of TIGIT, TGFB1 and KIR3DL2, indicative of a regulatory phenotype. In the memory CD4+ population, there was induction of CTLA4, KLRG1, and TGFB whereas there was an induction of TGF-B1 in naïve CD4+ T cells. In monocytes, there was induction of genes (HLA-DP, HLA-DQ) that promote a less inflammatory immune response. No side effects were observed, and no subjects developed human anti-mouse antibodies., Conclusion: These findings demonstrate that nasal Foralumab is safe and immunologically active in humans and presents a new avenue for the treatment of autoimmune and CNS diseases., Competing Interests: WC was employed by Clementi, Ltd. HLW is chair of the scientific advisory board of Tiziana Life Sciences and received consulting fees and stock options from the company. KS is an employee of Tiziana Life Sciences. TC is a member of the scientific advisory board and serves as a consultant to Tiziana Life Sciences. CMB-A serves as a consultant to Tiziana Life Sciences. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Chitnis, Kaskow, Case, Hanus, Li, Varghese, Healy, Gauthier, Saraceno, Saxena, Lokhande, Moreira, Zurawski, Roditi, Bergmark, Giovannoni, Torti, Li, Quintana, Clementi, Shailubhai, Weiner and Baecher-Allan.)

In recent years, many studies have illustrated the significant role that non-coding RNA (ncRNA) plays in biological activities, in which lncRNA, miRNA and especially their interactions have been proved to affect many biological processes. Some in silico methods have been proposed and applied to identify novel lncRNA-miRNA interactions (LMIs), but there are still imperfections in their RNA representation and information extraction approaches, which imply there is still room for further improving their performances. Meanwhile, only a few of them are accessible at present, which limits their practical applications. The construction of a new tool for LMI prediction is thus imperative for the better understanding of their relevant biological mechanisms. This study proposed a novel method, ncRNAInter, for LMI prediction. A comprehensive strategy for RNA representation and an optimized deep learning algorithm of graph neural network were utilized in this study. ncRNAInter was robust and showed better performance of 26.7% higher Matthews correlation coefficient than existing reputable methods for human LMI prediction. In addition, ncRNAInter proved its universal applicability in dealing with LMIs from various species and successfully identified novel LMIs associated with various diseases, which further verified its effectiveness and usability. All source code and datasets are freely available at https://github.com/idrblab/ncRNAInter., (© The Author(s) 2022. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

To explore low-cost, high-efficiency, and noble-metal-free catalysts for electrocatalytic water splitting in both acidic and alkaline media, the metal-metal carbide Janus hierarchical structure comprising Mo and β -Mo 2 C embedded on a carbon layer (Mo/ β -Mo 2 C)@C is synthesized by a hydrothermal reaction and subsequent low-temperature magnesium thermic process. Systematic characterization by XRD, XPS, Raman scattering, and SEM/TEM reveals the successful formation of metallic Mo and β -Mo 2 C nanoparticles. The synthesized (Mo/ β -Mo 2 C)@C has a large specific surface area and boasts highly efficient hydrogen evolution reaction activity including low overpotentials of 152 and 171 mV at a current density of 10 mA cm -2 and small Tafel slopes of 51.7 and 63.5 mV dec -1 in acidic and alkaline media, respectively. In addition, the catalyst shows outstanding stability for 48 h in both acidic and alkaline media. The excellent catalytic activity originates from more active sites and greater electron conductivity bestowed by the carbon layer, which also improves the long-term stability in both acidic and alkaline solutions., (© 2022 IOP Publishing Ltd.)

Genome-wide association studies have identified risk loci linked to inflammatory bowel disease (IBD) 1 -a complex chronic inflammatory disorder of the gastrointestinal tract. The increasing prevalence of IBD in industrialized countries and the augmented disease risk observed in migrants who move into areas of higher disease prevalence suggest that environmental factors are also important determinants of IBD susceptibility and severity 2 . However, the identification of environmental factors relevant to IBD and the mechanisms by which they influence disease has been hampered by the lack of platforms for their systematic investigation. Here we describe an integrated systems approach, combining publicly available databases, zebrafish chemical screens, machine learning and mouse preclinical models to identify environmental factors that control intestinal inflammation. This approach established that the herbicide propyzamide increases inflammation in the small and large intestine. Moreover, we show that an AHR-NF-κB-C/EBPβ signalling axis operates in T cells and dendritic cells to promote intestinal inflammation, and is targeted by propyzamide. In conclusion, we developed a pipeline for the identification of environmental factors and mechanisms of pathogenesis in IBD and, potentially, other inflammatory diseases., (© 2022. The Author(s), under exclusive licence to Springer Nature Limited.)

In a drug formulation (DFM), the major components by mass are not Active Pharmaceutical Ingredient (API) but rather Drug Inactive Ingredients (DIGs). DIGs can reach much higher concentrations than that achieved by API, which raises great concerns about their clinical toxicities. Therefore, the biological activities of DIG on physiologically relevant target are widely demanded by both clinical investigation and pharmaceutical industry. However, such activity data are not available in any existing pharmaceutical knowledge base, and their potentials in predicting the DIG-target interaction have not been evaluated yet. In this study, the comprehensive assessment and analysis on the biological activities of DIGs were therefore conducted. First, the largest number of DIGs and DFMs were systematically curated and confirmed based on all drugs approved by US Food and Drug Administration. Second, comprehensive activities for both DIGs and DFMs were provided for the first time to pharmaceutical community. Third, the biological targets of each DIG and formulation were fully referenced to available databases that described their pharmaceutical/biological characteristics. Finally, a variety of popular artificial intelligence techniques were used to assess the predictive potential of DIGs' activity data, which was the first evaluation on the possibility to predict DIG's activity. As the activities of DIGs are critical for current pharmaceutical studies, this work is expected to have significant implications for the future practice of drug discovery and precision medicine., (© The Author(s) 2022. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Background: Glioblastoma is a treatment-resistant brain cancer. Its hierarchical cellular nature and its tumor microenvironment (TME) before, during, and after treatments remain unresolved., Methods: Here, we used single-cell RNA sequencing to analyze new and recurrent glioblastoma and the nearby subventricular zone (SVZ)., Results: We found 4 glioblastoma neural lineages are present in new and recurrent glioblastoma with an enrichment of the cancer mesenchymal lineage, immune cells, and reactive astrocytes in early recurrences. Cancer lineages were hierarchically organized around cycling oligodendrocytic and astrocytic progenitors that are transcriptomically similar but distinct to SVZ neural stem cells (NSCs). Furthermore, NSCs from the SVZ of patients with glioblastoma harbored glioblastoma chromosomal anomalies. Lastly, mesenchymal cancer cells and TME reactive astrocytes shared similar gene signatures which were induced by radiotherapy in a myeloid-dependent fashion in vivo., Conclusion: These data reveal the dynamic, immune-dependent nature of glioblastoma's response to treatments and identify distant NSCs as likely cells of origin., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Multiomics is a powerful technique in molecular biology that facilitates the identification of new associations among different molecules (genes, proteins & metabolites). It has attracted tremendous research interest from the scientists worldwide and has led to an explosive number of published studies. Most of these studies are based on the regulation data provided in available databases. Therefore, it is essential to have molecular regulation data that are strictly validated in the living systems of various cell lines and in vivo models. However, no database has been developed yet to provide comprehensive molecular regulation information validated by living systems. Herein, a new database, Molecular Regulation Data of Living System Facilitating Multiomics Study (REGLIV) is introduced to describe various types of molecular regulation tested by the living systems. (1) A total of 2996 regulations describe the changes in 1109 metabolites triggered by alterations in 284 genes or proteins, and (2) 1179 regulations describe the variations in 926 proteins induced by 125 endogenous metabolites. Overall, REGLIV is unique in (a) providing the molecular regulation of a clearly defined regulatory direction other than simple correlation, (b) focusing on molecular regulations that are validated in a living system not simply in an in vitro test, and (c) describing the disease/tissue/species specific property underlying each regulation. Therefore, REGLIV has important implications for the future practice of not only multiomics, but also other fields relevant to molecular regulation. REGLIV is freely accessible at: https://idrblab.org/regliv/., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

The discovery of proper molecular signature from OMIC data is indispensable for determining biological state, physiological condition, disease etiology, and therapeutic response. However, the identified signature is reported to be highly inconsistent, and there is little overlap among the signatures identified from different biological datasets. Such inconsistency raises doubts about the reliability of reported signatures and significantly hampers its biological and clinical applications. Herein, an online tool, ConSIG, was constructed to realize consistent discovery of gene/protein signature from any uploaded transcriptomic/proteomic data. This tool is unique in a) integrating a novel strategy capable of significantly enhancing the consistency of signature discovery, b) determining the optimal signature by collective assessment, and c) confirming the biological relevance by enriching the disease/gene ontology. With the increasingly accumulated concerns about signature consistency and biological relevance, this online tool is expected to be used as an essential complement to other existing tools for OMIC-based signature discovery. ConSIG is freely accessible to all users without login requirement at https://idrblab.org/consig/., (© The Author(s) 2022. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Bioinformatic annotation of protein function is essential but extremely sophisticated, which asks for extensive efforts to develop effective prediction method. However, the existing methods tend to amplify the representativeness of the families with large number of proteins by misclassifying the proteins in the families with small number of proteins. That is to say, the ability of the existing methods to annotate proteins in the 'rare classes' remains limited. Herein, a new protein function annotation strategy, PFmulDL, integrating multiple deep learning methods, was thus constructed. First, the recurrent neural network was integrated, for the first time, with the convolutional neural network to facilitate the function annotation. Second, a transfer learning method was introduced to the model construction for further improving the prediction performances. Third, based on the latest data of Gene Ontology, the newly constructed model could annotate the largest number of protein families comparing with the existing methods. Finally, this newly constructed model was found capable of significantly elevating the prediction performance for the 'rare classes' without sacrificing that for the 'major classes'. All in all, due to the emerging requirements on improving the prediction performance for the proteins in 'rare classes', this new strategy would become an essential complement to the existing methods for protein function prediction. All the models and source codes are freely available and open to all users at: https://github.com/idrblab/PFmulDL., (Copyright © 2022. Published by Elsevier Ltd.)

Transcription factors (TFs) regulate gene expression by binding to DNA sequences and modulating transcriptional activity through their effector domains. Despite the central role of effector domains in TF function, there is a current lack of a comprehensive resource and characterization of effector domains. Here, we provide a catalog of 924 effector domains across 594 human TFs. Using this catalog, we characterized the amino acid composition of effector domains, their conservation across species and across the human population, and their roles in human diseases. Furthermore, we provide a classification system for effector domains that constitutes a valuable resource and a blueprint for future experimental studies of TF effector domain function., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2021 Elsevier Inc. All rights reserved.)

The success of protein engineering and design has extensively expanded the protein space, which presents a promising strategy for creating next-generation proteins of diverse functions. Among these proteins, the synthetic binding proteins (SBPs) are smaller, more stable, less immunogenic, and better of tissue penetration than others, which make the SBP-related data attracting extensive interest from worldwide scientists. However, no database has been developed to systematically provide the valuable information of SBPs yet. In this study, a database named 'Synthetic Binding Proteins for Research, Diagnosis, and Therapy (SYNBIP)' was thus introduced. This database is unique in (a) comprehensively describing thousands of SBPs from the perspectives of scaffolds, biophysical & functional properties, etc.; (b) panoramically illustrating the binding targets & the broad application of each SBP and (c) enabling a similarity search against the sequences of all SBPs and their binding targets. Since SBP is a human-made protein that has not been found in nature, the discovery of novel SBPs relied heavily on experimental protein engineering and could be greatly facilitated by in-silico studies (such as AI and computational modeling). Thus, the data provided in SYNBIP could lay a solid foundation for the future development of novel SBPs. The SYNBIP is accessible without login requirement at both official (https://idrblab.org/synbip/) and mirror (http://synbip.idrblab.net/) sites., (© The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Natural product (NP) has a long history in promoting modern drug discovery, which has derived or inspired a large number of currently prescribed drugs. Recently, the NPs have emerged as the ideal candidates to combine with other therapeutic strategies to deal with the persistent challenge of conventional therapy, and the molecular regulation mechanism underlying these combinations is crucial for the related communities. Thus, it is urgently demanded to comprehensively provide the disease-specific molecular regulation data for various NP-based drug combinations. However, no database has been developed yet to describe such valuable information. In this study, a newly developed database entitled 'Natural Product-based Drug Combination and Its Disease-specific Molecular Regulation (NPCDR)' was thus introduced. This database was unique in (a) providing the comprehensive information of NP-based drug combinations & describing their clinically or experimentally validated therapeutic effect, (b) giving the disease-specific molecular regulation data for a number of NP-based drug combinations, (c) fully referencing all NPs, drugs, regulated molecules/pathways by cross-linking them to the available databases describing their biological or pharmaceutical characteristics. Therefore, NPCDR is expected to have great implications for the future practice of network pharmacology, medical biochemistry, drug design, and medicinal chemistry. This database is now freely accessible without any login requirement at both official (https://idrblab.org/npcdr/) and mirror (http://npcdr.idrblab.net/) sites., (© The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.)

With the rapid progress in pharmaceutical experiments and clinical investigations, extensive knowledge of drug transporters (DTs) has accumulated, which is valuable data for the understanding of drug metabolism and disposition. However, such data are largely dispersed in the literature, which hampers its utility and significantly limits its possibility for comprehensive analysis. A variety of databases have, therefore, been constructed to provide DT-related data, and they were reviewed in this study. First, several knowledge bases providing data regarding clinically important drugs and their corresponding transporters were discussed, which constituted the most important resources of DT-centered data. Second, some databases describing the general transporters and their functional families were reviewed. Third, various databases offering transporter information as part of their entire data collection were described. Finally, customized database functions that are available to facilitate DT-related research were discussed. This review provided an overview of the whole collection of DT-related databases, which might facilitate research on precision medicine and rational drug use. SIGNIFICANCE STATEMENT: A collection of well established databases related to drug transporters were comprehensively reviewed, which were organized according to their importance in drug absorption, distribution, metabolism, and excretion research. These databases could collectively contribute to the research on rational drug use., Competing Interests: No author has an actual or perceived conflict of interest with the contents of this article., (Copyright © 2021 by The American Society for Pharmacology and Experimental Therapeutics.)

A typical output of a metabolomic experiment is a peak table corresponding to the intensity of measured signals. Peak table processing, an essential procedure in metabolomics, is characterized by its study dependency and combinatorial diversity. While various methods and tools have been developed to facilitate metabolomic data processing, it is challenging to determine which processing workflow will give good performance for a specific metabolomic study. NOREVA, an out-of-the-box protocol, was therefore developed to meet this challenge. First, the peak table is subjected to many processing workflows that consist of three to five defined calculations in combinatorially determined sequences. Second, the results of each workflow are judged against objective performance criteria. Third, various benchmarks are analyzed to highlight the uniqueness of this newly developed protocol in (1) evaluating the processing performance based on multiple criteria, (2) optimizing data processing by scanning thousands of workflows, and (3) allowing data processing for time-course and multiclass metabolomics. This protocol is implemented in an R package for convenient accessibility and to protect users' data privacy. Preliminary experience in R language would facilitate the usage of this protocol, and the execution time may vary from several minutes to a couple of hours depending on the size of the analyzed data., (© 2021. The Author(s), under exclusive licence to Springer Nature Limited.)

Coronavirus infection in humans is usually associated to respiratory tract illnesses, ranging in severity from mild to life-threatening respiratory failure. The aryl hydrocarbon receptor (AHR) was recently identified as a host factor for Zika and dengue viruses; AHR antagonists boost antiviral immunity, decrease viral titers and ameliorate Zika-induced pathology in vivo. Here we report that AHR is activated by infection with different coronaviruses, potentially impacting antiviral immunity and lung epithelial cells. Indeed, the analysis of single-cell RNA-seq from lung tissue detected increased expression of AHR and AHR transcriptional targets, suggesting AHR signaling activation in SARS-CoV-2-infected epithelial cells from COVID-19 patients. Moreover, we detected an association between AHR expression and viral load in SARS-CoV-2 infected patients. Finally, we found that the pharmacological inhibition of AHR suppressed the replication in vitro of one of the causative agents of the common cold, HCoV-229E, and the causative agent of the COVID-19 pandemic, SARS-CoV-2. Taken together, these findings suggest that AHR activation is a common strategy used by coronaviruses to evade antiviral immunity and promote viral replication, which may also contribute to lung pathology. Future studies should further evaluate the potential of AHR as a target for host-directed antiviral therapy., (© 2021. The Author(s).)

Inflammatory bowel disease (IBD) is a complex chronic inflammatory disorder of the gastrointestinal tract. Extracellular adenosine triphosphate (eATP) produced by the commensal microbiota and host cells activates purinergic signaling, promoting intestinal inflammation and pathology. Based on the role of eATP in intestinal inflammation, we developed yeast-based engineered probiotics that express a human P2Y2 purinergic receptor with up to a 1,000-fold increase in eATP sensitivity. We linked the activation of this engineered P2Y2 receptor to the secretion of the ATP-degrading enzyme apyrase, thus creating engineered yeast probiotics capable of sensing a pro-inflammatory molecule and generating a proportional self-regulated response aimed at its neutralization. These self-tunable yeast probiotics suppressed intestinal inflammation in mouse models of IBD, reducing intestinal fibrosis and dysbiosis with an efficacy similar to or higher than that of standard-of-care therapies usually associated with notable adverse events. By combining directed evolution and synthetic gene circuits, we developed a unique self-modulatory platform for the treatment of IBD and potentially other inflammation-driven pathologies., (© 2021. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Treatment of the cytokine release syndrome (CRS) has become an important part of rescuing hospitalized COVID-19 patients. Here, we systematically explored the transcriptional regulators of inflammatory cytokines involved in the COVID-19 CRS to identify candidate transcription factors (TFs) for therapeutic targeting using approved drugs. We integrated a resource of TF-cytokine gene interactions with single-cell RNA-seq expression data from bronchoalveolar lavage fluid cells of COVID-19 patients. We found 581 significantly correlated interactions, between 95 TFs and 16 cytokines upregulated in the COVID-19 patients, that may contribute to pathogenesis of the disease. Among these, we identified 19 TFs that are targets of FDA approved drugs. We investigated the potential therapeutic effect of 10 drugs and 25 drugs combinations on inflammatory cytokine production, which revealed two drugs that inhibited cytokine production and numerous combinations that show synergistic efficacy in downregulating cytokine production. Further studies of these candidate repurposable drugs could lead to a therapeutic regimen to treat the CRS in COVID-19 patients., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Santoso, Li, Rottenberg, Liu, Shen and Fuxman Bass.)

Cell-cell interactions control the physiology and pathology of the central nervous system (CNS). To study astrocyte cell interactions in vivo, we developed rabies barcode interaction detection followed by sequencing (RABID-seq), which combines barcoded viral tracing and single-cell RNA sequencing (scRNA-seq). Using RABID-seq, we identified axon guidance molecules as candidate mediators of microglia-astrocyte interactions that promote CNS pathology in experimental autoimmune encephalomyelitis (EAE) and, potentially, multiple sclerosis (MS). In vivo cell-specific genetic perturbation EAE studies, in vitro systems, and the analysis of MS scRNA-seq datasets and CNS tissue established that Sema4D and Ephrin-B3 expressed in microglia control astrocyte responses via PlexinB2 and EphB3, respectively. Furthermore, a CNS-penetrant EphB3 inhibitor suppressed astrocyte and microglia proinflammatory responses and ameliorated EAE. In summary, RABID-seq identified microglia-astrocyte interactions and candidate therapeutic targets., (Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

Astrocytes are glial cells that are abundant in the central nervous system (CNS) and that have important homeostatic and disease-promoting functions 1 . However, little is known about the homeostatic anti-inflammatory activities of astrocytes and their regulation. Here, using high-throughput flow cytometry screening, single-cell RNA sequencing and CRISPR-Cas9-based cell-specific in vivo genetic perturbations in mice, we identify a subset of astrocytes that expresses the lysosomal protein LAMP1 2 and the death receptor ligand TRAIL 3 . LAMP1 + TRAIL + astrocytes limit inflammation in the CNS by inducing T cell apoptosis through TRAIL-DR5 signalling. In homeostatic conditions, the expression of TRAIL in astrocytes is driven by interferon-γ (IFNγ) produced by meningeal natural killer (NK) cells, in which IFNγ expression is modulated by the gut microbiome. TRAIL expression in astrocytes is repressed by molecules produced by T cells and microglia in the context of inflammation. Altogether, we show that LAMP1 + TRAIL + astrocytes limit CNS inflammation by inducing T cell apoptosis, and that this astrocyte subset is maintained by meningeal IFNγ + NK cells that are licensed by the microbiome.

Treatment of the cytokine release syndrome (CRS) has become an important part of rescuing hospitalized COVID-19 patients. Here, we systematically explored the transcriptional regulators of inflammatory cytokines involved in the COVID-19 CRS to identify candidate transcription factors (TFs) for therapeutic targeting using approved drugs. We integrated a resource of TF-cytokine gene interactions with single-cell RNA-seq expression data from bronchoalveolar lavage fluid cells of COVID-19 patients. We found 581 significantly correlated interactions, between 95 TFs and 16 cytokines upregulated in the COVID-19 patients, that may contribute to pathogenesis of the disease. Among these, we identified 19 TFs that are targets of FDA approved drugs. We investigated the potential therapeutic effect of 10 drugs and 25 drug combinations on inflammatory cytokine production in peripheral blood mononuclear cells, which revealed two drugs that inhibited cytokine production and numerous combinations that show synergistic efficacy in downregulating cytokine production. Further studies of these candidate repurposable drugs could lead to a therapeutic regimen to treat the CRS in COVID-19 patients.

Therapeutic approaches for the induction of immune tolerance remain an unmet clinical need for the treatment of autoimmune diseases, including multiple sclerosis (MS). Based on its role in the control of the immune response, the ligand-activated transcription factor aryl hydrocarbon receptor (AhR) is a candidate target for novel immunotherapies. Here, we report the development of AhR-activating nanoliposomes (NLPs) to induce antigen-specific tolerance. NLPs loaded with the AhR agonist ITE and a T cell epitope from myelin oligodendrocyte glycoprotein (MOG) 35-55 induced tolerogenic dendritic cells and suppressed the development of experimental autoimmune encephalomyelitis (EAE), a preclinical model of MS, in preventive and therapeutic setups. EAE suppression was associated with the expansion of MOG 35-55 -specific FoxP3 + regulatory T cells (Treg cells) and type 1 regulatory T cells (Tr1 cells), concomitant with a reduction in central nervous system-infiltrating effector T cells (Teff cells). Notably, NLPs induced bystander suppression in the EAE model established in C57BL/6 × SJL F1 mice. Moreover, NLPs ameliorated chronic progressive EAE in nonobese diabetic mice, a model which resembles some aspects of secondary progressive MS. In summary, these studies describe a platform for the therapeutic induction of antigen-specific tolerance in autoimmune diseases., Competing Interests: Competing interest statement: J.E.K, A.J., N.K., S.T., D.N., A.P., V.P.S. are/were employees at AnTolRx; F.J.Q. is a consultant at AnTolRx. This work was partially funded by AnTolRx.

Proper cytokine gene expression is essential in development, homeostasis and immune responses. Studies on the transcriptional control of cytokine genes have mostly focused on highly researched transcription factors (TFs) and cytokines, resulting in an incomplete portrait of cytokine gene regulation. Here, we used enhanced yeast one-hybrid (eY1H) assays to derive a comprehensive network comprising 1380 interactions between 265 TFs and 108 cytokine gene promoters. Our eY1H-derived network greatly expands the known repertoire of TF-cytokine gene interactions and the set of TFs known to regulate cytokine genes. We found an enrichment of nuclear receptors and confirmed their role in cytokine regulation in primary macrophages. Additionally, we used the eY1H-derived network as a framework to identify pairs of TFs that can be targeted with commercially-available drugs to synergistically modulate cytokine production. Finally, we integrated the eY1H data with single cell RNA-seq and phenotypic datasets to identify novel TF-cytokine regulatory axes in immune diseases and immune cell lineage development. Overall, the eY1H data provides a rich resource to study cytokine regulation in a variety of physiological and disease contexts., (© The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Analyzing every cell in a diverse sample provides insight into population-level heterogeneity, but abundant cell types dominate the analysis and rarer populations are scarcely represented in the data. To focus on specific cell types, the current paradigm is to physically isolate subsets of interest prior to analysis; however, it remains difficult to isolate and then single-cell sequence such populations because of compounding losses. Here, we describe an alternative approach that selectively merges cells with reagents to achieve enzymatic reactions without having to physically isolate cells. We apply this technique to perform single-cell transcriptome and genome sequencing of specific cell subsets. Our method for analyzing heterogeneous populations obviates the need for pre- or post-enrichment and simplifies single-cell workflows, making it useful for other applications in single-cell biology, combinatorial chemical synthesis, and drug screening.

Zika virus (ZIKV) is a flavivirus linked to multiple birth defects including microcephaly, known as congenital ZIKV syndrome. The identification of host factors involved in ZIKV replication may guide efficacious therapeutic interventions. In genome-wide transcriptional studies, we found that ZIKV infection triggers aryl hydrocarbon receptor (AHR) activation. Specifically, ZIKV infection induces kynurenine (Kyn) production, which activates AHR, limiting the production of type I interferons (IFN-I) involved in antiviral immunity. Moreover, ZIKV-triggered AHR activation suppresses intrinsic immunity driven by the promyelocytic leukemia (PML) protein, which limits ZIKV replication. AHR inhibition suppressed the replication of multiple ZIKV strains in vitro and also suppressed replication of the related flavivirus dengue. Finally, AHR inhibition with a nanoparticle-delivered AHR antagonist or an inhibitor developed for human use limited ZIKV replication and ameliorated newborn microcephaly in a murine model. In summary, we identified AHR as a host factor for ZIKV replication and PML protein as a driver of anti-ZIKV intrinsic immunity.

Coronavirus infection is associated to life-threatening respiratory failure. The aryl hydrocarbon receptor (AHR) was recently identified as a host factor for Zika and dengue viruses; AHR antagonists decrease viral titers and ameliorate ZIKV-induced pathology in vivo . Here we report that AHR is activated during coronavirus infection, impacting anti-viral immunity and lung basal cells associated to tissue repair. Hence, AHR antagonists are candidate therapeutics for the management of coronavirus-infected patients., Competing Interests: Competing financial interests FJQ is a member of the Scientific Advisory Board of Kyn Therapeutics. The other authors declare no competing interests.

Multiple sclerosis is a chronic inflammatory disease of the CNS 1 . Astrocytes contribute to the pathogenesis of multiple sclerosis 2 , but little is known about the heterogeneity of astrocytes and its regulation. Here we report the analysis of astrocytes in multiple sclerosis and its preclinical model experimental autoimmune encephalomyelitis (EAE) by single-cell RNA sequencing in combination with cell-specific Ribotag RNA profiling, assay for transposase-accessible chromatin with sequencing (ATAC-seq), chromatin immunoprecipitation with sequencing (ChIP-seq), genome-wide analysis of DNA methylation and in vivo CRISPR-Cas9-based genetic perturbations. We identified astrocytes in EAE and multiple sclerosis that were characterized by decreased expression of NRF2 and increased expression of MAFG, which cooperates with MAT2α to promote DNA methylation and represses antioxidant and anti-inflammatory transcriptional programs. Granulocyte-macrophage colony-stimulating factor (GM-CSF) signalling in astrocytes drives the expression of MAFG and MAT2α and pro-inflammatory transcriptional modules, contributing to CNS pathology in EAE and, potentially, multiple sclerosis. Our results identify candidate therapeutic targets in multiple sclerosis.

MicroRNAs were demonstrated to play an important role in the regulation of gene expression. Here, we showed that miR-99a and -99b (miR-99a/b) were down-regulated in human cervical cancer patient tissues and were negatively related with lymphatic metastasis. In addition, overexpression of miR-99a/b inhibited cell growth and invasion, whereas suppression of miR-99a/b yielded the reverse phenotype. Dual luciferase report assay revealed that mTOR was identified as a novel target gene of both miR-99a and -99b. Altogether, these results suggested that miR-99a/b directly and negatively regulated mTOR expression in cervical cancer cells, and enforced the importance of miR-99a/b and their targets in the malignant phenotypes of cervical carcinogenesis.