exRNA Atlas Analysis Reveals Distinct Extracellular RNA Cargo Types and Their Carriers Present across Human Biofluids.

To develop a map of cell-cell communication mediated by extracellular RNA (exRNA), the NIH Extracellular RNA Communication Consortium created the exRNA Atlas resource (https://exrna-atlas.org). The Atlas version 4P1 hosts 5,309 exRNA-seq and exRNA qPCR profiles from 19 studies and a suite of analysis and visualization tools. To analyze variation between profiles, we apply computational deconvolution. The analysis leads to a model with six exRNA cargo types (CT1, CT2, CT3A, CT3B, CT3C, CT4), each detectable in multiple biofluids (serum, plasma, CSF, saliva, urine). Five of the cargo types associate with known vesicular and non-vesicular (lipoprotein and ribonucleoprotein) exRNA carriers. To validate utility of this model, we re-analyze an exercise response study by deconvolution to identify physiologically relevant response pathways that were not detected previously. To enable wide application of this model, as part of the exRNA Atlas resource, we provide tools for deconvolution and analysis of user-provided case-control studies.

Outbreak.info Research Library: a standardized, searchable platform to discover and explore COVID-19 resources.

Outbreak.info Research Library is a standardized, searchable interface of coronavirus disease 2019 (COVID-19) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) publications, clinical trials, datasets, protocols and other resources, built with a reusable framework. We developed a rigorous schema to enforce consistency across different sources and resource types and linked related resources. Researchers can quickly search the latest research across data repositories, regardless of resource type or repository location, via a search interface, public application programming interface (API) and R package.

Outbreak.info genomic reports: scalable and dynamic surveillance of SARS-CoV-2 variants and mutations.

In response to the emergence of SARS-CoV-2 variants of concern, the global scientific community, through unprecedented effort, has sequenced and shared over 11 million genomes through GISAID, as of May 2022. This extraordinarily high sampling rate provides a unique opportunity to track the evolution of the virus in near real-time. Here, we present outbreak.info , a platform that currently tracks over 40 million combinations of Pango lineages and individual mutations, across over 7,000 locations, to provide insights for researchers, public health officials and the general public. We describe the interpretable visualizations available in our web application, the pipelines that enable the scalable ingestion of heterogeneous sources of SARS-CoV-2 variant data and the server infrastructure that enables widespread data dissemination via a high-performance API that can be accessed using an R package. We show how outbreak.info can be used for genomic surveillance and as a hypothesis-generation tool to understand the ongoing pandemic at varying geographic and temporal scales.

MyGeneset.info: an interactive and programmatic platform for community-curated and user-created collections of genes.

Gene definitions and identifiers can be painful to manage-more so when trying to include gene function annotations as this can be highly context-dependent. Creating groups of genes or gene sets can help provide such context, but it compounds the issue as each gene within the gene set can map to multiple identifiers and have annotations derived from multiple sources. We developed MyGeneset.info to provide an API for integrated annotations for gene sets suitable for use in analytical pipelines or web servers. Leveraging our previous work with MyGene.info (a server that provides gene-centric annotations and identifiers), MyGeneset.info addresses the challenge of managing gene sets from multiple resources. With our API, users readily have read-only access to gene sets imported from commonly-used resources such as Wikipathways, CTD, Reactome, SMPDB, MSigDB, GO, and DO. In addition to supporting the access and reuse of approximately 180k gene sets from humans, common model organisms (mice, yeast, etc.), and less-common ones (e.g. black cottonwood tree), MyGeneset.info supports user-created gene sets, providing an important means for making gene sets more FAIR. User-created gene sets can serve as a way to store and manage collections for analysis or easy dissemination through a consistent API.

BioThings Explorer: a query engine for a federated knowledge graph of biomedical APIs.

SUMMARY: Knowledge graphs are an increasingly common data structure for representing biomedical information. These knowledge graphs can easily represent heterogeneous types of information, and many algorithms and tools exist for querying and analyzing graphs. Biomedical knowledge graphs have been used in a variety of applications, including drug repurposing, identification of drug targets, prediction of drug side effects, and clinical decision support. Typically, knowledge graphs are constructed by centralization and integration of data from multiple disparate sources. Here, we describe BioThings Explorer, an application that can query a virtual, federated knowledge graph derived from the aggregated information in a network of biomedical web services. BioThings Explorer leverages semantically precise annotations of the inputs and outputs for each resource, and automates the chaining of web service calls to execute multi-step graph queries. Because there is no large, centralized knowledge graph to maintain, BioThings Explorer is distributed as a lightweight application that dynamically retrieves information at query time. AVAILABILITY AND IMPLEMENTATION: More information can be found at https://explorer.biothings.io and code is available at https://github.com/biothings/biothings_explorer.

Diverse reprogramming codes for neuronal identity.

The transcriptional programs that establish neuronal identity evolved to produce the rich diversity of neuronal cell types that arise sequentially during development. Remarkably, transient expression of certain transcription factors can also endow non-neural cells with neuronal properties. The relationship between reprogramming factors and the transcriptional networks that produce neuronal identity and diversity remains largely unknown. Here, from a screen of 598 pairs of transcription factors, we identify 76 pairs of transcription factors that induce mouse fibroblasts to differentiate into cells with neuronal features. By comparing the transcriptomes of these induced neuronal cells (iN cells) with those of endogenous neurons, we define a 'core' cell-autonomous neuronal signature. The iN cells also exhibit diversity; each transcription factor pair produces iN cells with unique transcriptional patterns that can predict their pharmacological responses. By linking distinct transcription factor input 'codes' to defined transcriptional outputs, this study delineates cell-autonomous features of neuronal identity and diversity and expands the reprogramming toolbox to facilitate engineering of induced neurons with desired patterns of gene expression and related functional properties.

Schema Playground: a tool for authoring, extending, and using metadata schemas to improve FAIRness of biomedical data.

BACKGROUND: Biomedical researchers are strongly encouraged to make their research outputs more Findable, Accessible, Interoperable, and Reusable (FAIR). While many biomedical research outputs are more readily accessible through open data efforts, finding relevant outputs remains a significant challenge. Schema.org is a metadata vocabulary standardization project that enables web content creators to make their content more FAIR. Leveraging Schema.org could benefit biomedical research resource providers, but it can be challenging to apply Schema.org standards to biomedical research outputs. We created an online browser-based tool that empowers researchers and repository developers to utilize Schema.org or other biomedical schema projects. RESULTS: Our browser-based tool includes features which can help address many of the barriers towards Schema.org-compliance such as: The ability to easily browse for relevant Schema.org classes, the ability to extend and customize a class to be more suitable for biomedical research outputs, the ability to create data validation to ensure adherence of a research output to a customized class, and the ability to register a custom class to our schema registry enabling others to search and re-use it. We demonstrate the use of our tool with the creation of the Outbreak.info schema-a large multi-class schema for harmonizing various COVID-19 related resources. CONCLUSIONS: We have created a browser-based tool to empower biomedical research resource providers to leverage Schema.org classes to make their research outputs more FAIR.

BioThings SDK: a toolkit for building high-performance data APIs in biomedical research.

SUMMARY: To meet the increased need of making biomedical resources more accessible and reusable, Web Application Programming Interfaces (APIs) or web services have become a common way to disseminate knowledge sources. The BioThings APIs are a collection of high-performance, scalable, annotation as a service APIs that automate the integration of biological annotations from disparate data sources. This collection of APIs currently includes MyGene.info, MyVariant.info and MyChem.info for integrating annotations on genes, variants and chemical compounds, respectively. These APIs are used by both individual researchers and application developers to simplify the process of annotation retrieval and identifier mapping. Here, we describe the BioThings Software Development Kit (SDK), a generalizable and reusable toolkit for integrating data from multiple disparate data sources and creating high-performance APIs. This toolkit allows users to easily create their own BioThings APIs for any data type of interest to them, as well as keep APIs up-to-date with their underlying data sources. AVAILABILITY AND IMPLEMENTATION: The BioThings SDK is built in Python and released via PyPI (https://pypi.org/project/biothings/). Its source code is hosted at its github repository (https://github.com/biothings/biothings.api). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Recent advances in targeting leucine-rich repeat kinase 2 as a potential strategy for the treatment of Parkinson's disease.

Parkinson's disease (PD) is the second most common neurodegenerative disease. Several single gene mutations involved in PD have been identified such as leucine-rich repeat kinase 2 (LRRK2), the most common cause of sporadic and familial PD. Its mutations have attracted much attention to therapeutically targeting this kinase. To date, many compounds including small chemical molecules with diverse scaffolds and RNA agents have been developed with significant amelioration in preclinical PD models. Currently, five candidates, DNL201, DNL151, WXWH0226, NEU-723 and BIIB094, have advanced to clinical trials for PD treatment. In this review, we describe the structure, pathogenic mutations and the mechanism of LRRK2, and summarize the development of LRRK2 inhibitors in preclinical and clinical studies, trying to provide an insight into targeting LRRK2 for PD intervention in future.

Switchable and Highly Robust Ultralong Room-Temperature Phosphorescence from Polymer-Based Transparent Films with Three-Dimensional Covalent Networks for Erasable Light Printing.

In this work, an efficient polymer-based organic afterglow system, which shows reversible photochromism, switchable ultralong organic phosphorescence (UOP), and prominent water and chemical resistance simultaneously, has been developed for the first time. By doping phenoxazine (PXZ) and 10-ethyl-10H-phenoxazine (PXZEt) into epoxy polymers, the resulting PXZ@EP-0.25 % and PXZEt@EP-0.25 % films show unique photoactivated UOP properties, with phosphorescence quantum yields and lifetimes up to 10.8 % and 845 ms, respectively. It is found that the steady-state luminescence and UOP of PXZ@EP-0.25 % are switchable by light irradiation and thermal annealing. Moreover, the doped films can still produce conspicuous UOP after soaking in water, strong acid and base, and organic solvents for more than two weeks, exhibiting outstanding water and chemical resistance. Inspired by these exciting results, the PXZ@EP-0.25 % has been successfully exploited as an erasable transparent film for light printing.

Diastereoselective Access to Triazolo[1,2-a]indolines via a Bio-Inspired Oxidative Cyclization of NH-Indoles.

Establishing three-dimensional chemicals by using the C2-C3 π bond of indoles has always been a research hotspot in organic synthesis; however, employing the oxidative C2-C3 π bond of indoles to generate imine which would lead to the N1-C2 π bond cyclization under metal-free conditions is still rare. Here, we report a bio-inspired synthesis of triazolo[1,2-a]indolines by the oxidative cyclization between NH-indoles and azomethine imines with 3,3-dimethyldioxirane as the sole oxidant under metal-free and mild conditions. This finding represents an elegant instance of tri-functionalization of NH-indoles, which provides rapid access to a broad range of triazolo[1,2-a]indolines with tetrahydroisoquinolines in one single step. Up to 86% yield and above 20:1 dr value are observed. The radical mechanism and proton migration process have been speculated.

Treating Autoimmune Diseases by Targeting IL-23 with Gene-Silencing Pyrrole-Imidazole Polyamide.

Autoimmune diseases are a physiological state that immune responses are directed against and damage the body's own tissues. Numerous studies have demonstrated promising therapeutic effects in certain autoimmune diseases by targeting IL-23/IL-17 axis, mostly through using Abs against IL-23 or IL-17A. Pyrrole-imidazole polyamides are nuclease-resistant compounds that inhibit gene expression through binding to the minor groove of DNA. To develop a novel gene-silencing agent that targets IL-23/IL-17 axis, we designed polyamide that specifically binds to the transcription factor c-Rel-binding site located in the promoter of IL-23p19 subunit. Our study showed that this polyamide is capable of entering into nucleus with high efficiency in dendritic cells and macrophage. In addition, it prevented the binding of c-Rel to the promoter of IL-23p19 in vivo and specifically inhibited the expression of IL-23. More importantly, we demonstrated that this polyamide is therapeutically effective using both the imiquimod-induced psoriasis and experimental autoimmune uveitis mouse models. Taken together, these results indicate that pyrrole-imidazole polyamide targeting IL-23p19 could be a novel and feasible therapeutic strategy for patients with autoimmune diseases.

A novel pyrrole-imidazole polyamide targets Aurora kinase A and suppresses tumor growth in vivo.

Aurora kinase A (Aurora A) plays a critical role in regulating cell mitotic progression and has been considered as a promising drug target for cancer therapy. To develop a novel molecule targeting Aurora A with high selectivity and efficacy, we designed and synthesized a pyrrole-imidazole polyamide (PIP) Hoechst conjugate, PIP-Ht, targeting to a cell-cycle regulated DNA sequence locating at the promoter of human Aurora A gene (AURKA). PIP-Ht potently suppressed AURKA promoter activities, mRNA expression and protein level, induced tumor cell cycle delay and inhibited tumor cell proliferation in vitro. Furthermore, subcutaneous injection of PIP-Ht into mice bearing human cancer xenografts induced significant tumor growth suppression and cell apoptosis. Collectively, PIP-Ht exhibits the potential as an effective therapeutic candidate for the tumor treatment.

Coibamide A kills cancer cells through inhibiting autophagy.

Natural products are useful tools for biological mechanism research and drug discovery. Due to the excellent tumor cell growth inhibitory profile and sub-nanomolar potency, Coibamide A (CA), an N-methyl-stabilized depsipeptide isolated from marine cyanobacterium, has been considered as a promising lead compound for cancer treatment. However, the molecular anti-cancer mechanism of the action of CA remains unclear. Here, we showed that CA treatment induced caspase-independent cell death in breast cancer cells. CA treatment also led to severe lysosome defects, which was ascribed to the impaired glycosylation of lysosome membrane protein LAMP1 and LAMP2. As a consequence, the autophagosome-lysosome fusion was blocked upon CA treatment. In addition, we presented evidence that this autophagy defect partially contributed to the CA treatment-induced tumor cell death. Together, our work uncovers a novel mechanism underlying the anti-cancer action of CA, which will promote its further application for cancer therapy.

Waist-to-height ratio, an optimal anthropometric indicator for metabolic dysfunction associated fatty liver disease in the Western Chinese male population.

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) has been entitled as metabolic-dysfunction associated fatty liver disease (MAFLD). Therefore anthropometric indicators of adiposity may provide a non-invasive predictive and diagnostic tool for this disease. This study intended to validate and compare the MAFLD predictive and diagnostic capability of eight anthropometric indicators. METHODS: The study involved a population-based retrospective cross-sectional design. The Fangchenggang area male health and examination survey (FAMHES) was used to collect data of eight anthropometric indicators, involving body mass index (BMI), waist-to-height ratio (WHtR), waist-hip ratio (WHR), body adiposity index (BAI), cardiometabolic index (CMI), lipid accumulation product (LAP), visceral adiposity index (VAI), and abdominal volume index (AVI). Receiver operating characteristics (ROC) curves and the respective areas under the curves (AUCs) were utilized to compare the diagnostic capacity of each indicator for MAFLD and to determine the optimal cutoff points. Binary logistic regression analysis was applied to identify the odds ratios (OR) with 95% confidence intervals (95% CI) for all anthropometric indicators and MAFLD. The Spearman rank correlation coefficients of anthropometric indicators, sex hormones, and MAFLD were also calculated. RESULTS: All selected anthropometric indicators were significantly associated with MAFLD (P < 0.001), with an AUC above 0.79. LAP had the highest AUC [0.868 (95% CI, 0.853-0.883)], followed by WHtR [0.863 (95% CI, 0.848-0.879)] and AVI [0.859 (95% CI, 0.843-0.874)]. The cutoff values for WHtR, LAP and AVI were 0.49, 24.29, and 13.61, respectively. WHtR [OR 22.181 (95% CI, 16.216-30.340)] had the strongest association with MAFLD, regardless of potential confounders. Among all the anthropometric indicators, the strongest association was seen between LAP and sex hormones. CONCLUSION: All anthropometric indicators were associated with MAFLD. WHtR was identified as the strongest predictor of MAFLD in young Chinese males, followed by LAP and AVI. The strongest association was found between LAP and sex hormones.

A high resolution atlas of gene expression in the domestic sheep (Ovis aries).

Sheep are a key source of meat, milk and fibre for the global livestock sector, and an important biomedical model. Global analysis of gene expression across multiple tissues has aided genome annotation and supported functional annotation of mammalian genes. We present a large-scale RNA-Seq dataset representing all the major organ systems from adult sheep and from several juvenile, neonatal and prenatal developmental time points. The Ovis aries reference genome (Oar v3.1) includes 27,504 genes (20,921 protein coding), of which 25,350 (19,921 protein coding) had detectable expression in at least one tissue in the sheep gene expression atlas dataset. Network-based cluster analysis of this dataset grouped genes according to their expression pattern. The principle of 'guilt by association' was used to infer the function of uncharacterised genes from their co-expression with genes of known function. We describe the overall transcriptional signatures present in the sheep gene expression atlas and assign those signatures, where possible, to specific cell populations or pathways. The findings are related to innate immunity by focusing on clusters with an immune signature, and to the advantages of cross-breeding by examining the patterns of genes exhibiting the greatest expression differences between purebred and crossbred animals. This high-resolution gene expression atlas for sheep is, to our knowledge, the largest transcriptomic dataset from any livestock species to date. It provides a resource to improve the annotation of the current reference genome for sheep, presenting a model transcriptome for ruminants and insight into gene, cell and tissue function at multiple developmental stages.

Effects of Temperature and Ionic Concentration on Nanodroplet Electrocoalescence.

Droplet electrocoalescence is of interest for various applications such as petroleum dehydration, electrospray ionization, and surface self-cleaning. Here, the effects of temperature and ionic concentration on nanodroplet electrocoalescence are investigated by molecular dynamics simulation. The results show that low ionic concentration rapidly drives ions towards water clusters and leads to dipole polarization of droplets. With an increase of ionic concentration, the particle-particle interaction is enhanced, but the mobility of free water molecules and salt ions is curbed by hydration and ion pairs, which then slows the electrocoalescence. Low temperature accelerates the rotation of water molecules but does not enhance the mobility of ions. Alternatively, high temperature not only breaks the self-assembly of water molecules along the electric field direction but also helps ions to overcome the electrostatic barrier between particles. The latter effect promotes dipole polarization to compensate for the shortcoming of less orientation polarization. The combined effects of ion concentration and temperature are investigated and unified by droplet conductivity from the microscopic point of view. The conductivity increases with the increase in temperatures and ionic concentrations. We confirm that the accurate control of droplet electrocoalescence can be achieved by a suitable combination of temperature and ionic concentration.

Cross-linking BioThings APIs through JSON-LD to facilitate knowledge exploration.

BACKGROUND: Application Programming Interfaces (APIs) are now widely used to distribute biological data. And many popular biological APIs developed by many different research teams have adopted Javascript Object Notation (JSON) as their primary data format. While usage of a common data format offers significant advantages, that alone is not sufficient for rich integrative queries across APIs. RESULTS: Here, we have implemented JSON for Linking Data (JSON-LD) technology on the BioThings APIs that we have developed, MyGene.info , MyVariant.info and MyChem.info . JSON-LD provides a standard way to add semantic context to the existing JSON data structure, for the purpose of enhancing the interoperability between APIs. We demonstrated several use cases that were facilitated by semantic annotations using JSON-LD, including simpler and more precise query capabilities as well as API cross-linking. CONCLUSIONS: We believe that this pattern offers a generalizable solution for interoperability of APIs in the life sciences.

Combination of novel and public RNA-seq datasets to generate an mRNA expression atlas for the domestic chicken.

BACKGROUND: The domestic chicken (Gallus gallus) is widely used as a model in developmental biology and is also an important livestock species. We describe a novel approach to data integration to generate an mRNA expression atlas for the chicken spanning major tissue types and developmental stages, using a diverse range of publicly-archived RNA-seq datasets and new data derived from immune cells and tissues. RESULTS: Randomly down-sampling RNA-seq datasets to a common depth and quantifying expression against a reference transcriptome using the mRNA quantitation tool Kallisto ensured that disparate datasets explored comparable transcriptomic space. The network analysis tool Graphia was used to extract clusters of co-expressed genes from the resulting expression atlas, many of which were tissue or cell-type restricted, contained transcription factors that have previously been implicated in their regulation, or were otherwise associated with biological processes, such as the cell cycle. The atlas provides a resource for the functional annotation of genes that currently have only a locus ID. We cross-referenced the RNA-seq atlas to a publicly available embryonic Cap Analysis of Gene Expression (CAGE) dataset to infer the developmental time course of organ systems, and to identify a signature of the expansion of tissue macrophage populations during development. CONCLUSION: Expression profiles obtained from public RNA-seq datasets - despite being generated by different laboratories using different methodologies - can be made comparable to each other. This meta-analytic approach to RNA-seq can be extended with new datasets from novel tissues, and is applicable to any species.

LncRNA AWPPH inhibits SMAD4 via EZH2 to regulate bladder cancer progression.

This study aimed to investigate the effect and underlying mechanism of lncRNA AWPPH in bladder cancer (BC). A total of 20 Ta-T1 stage BC tissues, 20 T2-T4 stage BC tissues, and 20 normal bladder tissues, as well as human bladder epithelial cell line SV-HUC-1, human BC cell lines RT4, and T24 were obtained to detect the levels of AWPPH, enhancer of zeste homolog 2 (EZH2) and SMAD4 using RT-qPCR or Western blotting. RT4 cells were transfected with pc-AWPPH, pc-EZH2, or pc-control and T24 cells were transfected with si-AWPPH, si-EZH2, si-control, or pc-AWPPH + pc-SMAD4, respectively. Then, cell proliferation, apoptosis, autophagy, and migration, were detected using MTT assay, colony formation assay, Annexin V-FITC/PI method, Western blotting, and Transwell analysis, respectively. The relationship of AWPPH and EZH2 or SMAD4 was evaluated by RNA immunoprecipitation (RIP) assay or Chromatin immunoprecipitation (ChIP) assay. Compared with normal bladder tissues or cells, the levels of AWPPH and EZH2 were overexpressed, while SMAD4 was down-regulated in BC tissues or cells (all P < 0.01). Cell viability, colony number, and migration were significantly increased, while cell apoptosis ratio was reduced in cells with pc-AWPPH compared with cells with pc-control (all P < 0.05), meanwhile, these effects were reversed by the treatment of pc-SMAD4. Then, RIP assay revealed that AWPPH could bind to EZH2 and ChIP assay showed SMAD4 was regulated by EZH2. LncRNA AWPPH can promote cell proliferation, autophagy, and migration, as well as inhibit cell apoptosis in BC by inhibiting SMAD4 via EZH2.