Evgenii Ziaikin, Moran David, Sofya Uspenskaya, Masha Y Niv
{"title":"BitterDB: 2024 update on bitter ligands and taste receptors","authors":"Evgenii Ziaikin, Moran David, Sofya Uspenskaya, Masha Y Niv","doi":"10.1093/nar/gkae1044","DOIUrl":"https://doi.org/10.1093/nar/gkae1044","url":null,"abstract":"BitterDB (http://bitterdb.agri.huji.ac.il) was introduced in 2012 as a central resource for information on bitter-tasting molecules and their receptors, and was updated in 2019. The information in BitterDB is used for tasks such as exploring the bitter chemical space, choosing suitable ligands for experimental studies, analyzing receptors’ selectivity and promiscuity, and developing machine learning predictors for taste. Here, we describe a major upgrade of the database, including significant increase in content as well as new features. BitterDB now holds over 2200 bitter molecules. For ∼700 molecules, at least one associated bitter taste receptor (TAS2R) is reported. The overall number of ligand-TAS2R associations is now close to 1800. BitterDB is extended to a total of 66 species (including dog, birds, fishes and primates). Following advances in computational structure prediction by AlphaFold and related methods, and the experimental determination of TAS2R structures by cryo-electron microscopy, BitterDB provides links to available structures of TAS2Rs.","PeriodicalId":19471,"journal":{"name":"Nucleic Acids Research","volume":"129 2 1","pages":""},"PeriodicalIF":14.9,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142610561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xinyi Shen, Yintao Zhang, Jiamin Li, Ying Zhou, Samuel D Butensky, Yechi Zhang, Zongwei Cai, Andrew T DeWan, Sajid A Khan, Hong Yan, Caroline H Johnson, Feng Zhu
{"title":"OncoSexome: the landscape of sex-based differences in oncologic diseases","authors":"Xinyi Shen, Yintao Zhang, Jiamin Li, Ying Zhou, Samuel D Butensky, Yechi Zhang, Zongwei Cai, Andrew T DeWan, Sajid A Khan, Hong Yan, Caroline H Johnson, Feng Zhu","doi":"10.1093/nar/gkae1003","DOIUrl":"https://doi.org/10.1093/nar/gkae1003","url":null,"abstract":"The NIH policy on sex as biological variable (SABV) emphasized the importance of sex-based differences in precision oncology. Over 50% of clinically actionable oncology genes are sex-biased, indicating differences in drug efficacy. Research has identified sex differences in non-reproductive cancers, highlighting the need for comprehensive sex-based cancer data. We therefore developed OncoSexome, a multidimensional knowledge base describing sex-based differences in cancer (https://idrblab.org/OncoSexome/) across four key topics: antineoplastic drugs and responses (SDR), oncology-related biomarkers (SBM), risk factors (SRF) and microbial landscape (SML). SDR covers sex-based differences in 2051 anticancer drugs; SBM describes 12 551 sex-differential biomarkers; SRF illustrates 350 sex-dependent risk factors; SML demonstrates 1386 microbes with sex-differential abundances associated with cancer development. OncoSexome is unique in illuminating multifaceted influences of biological sex on cancer, providing both external and endogenous contributors to cancer development and describing sex-based differences for the broadest oncological classes. Given the increasing global research interest in sex-based differences, OncoSexome is expected to impact future precision oncology practices significantly.","PeriodicalId":19471,"journal":{"name":"Nucleic Acids Research","volume":"163 1","pages":""},"PeriodicalIF":14.9,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142610487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hayley Jackson, Eponine Oler, Claudia Torres-Calzada, Ray Kruger, Amandeep Singh Hira, Yamilé López-Hernández, Devanshi Pandit, Jiaxuan Wang, Kellie Yang, Omolola Fatokun, Mark Berjanskii, Scott MacKay, Tanvir Sajed, Scott Han, Robyn Woudstra, Gina Sykes, Jenna Poelzer, Aadhavya Sivakumaran, Vasuk Gautam, Gane Wong, David S Wishart
{"title":"MarkerDB 2.0: a comprehensive molecular biomarker database for 2025","authors":"Hayley Jackson, Eponine Oler, Claudia Torres-Calzada, Ray Kruger, Amandeep Singh Hira, Yamilé López-Hernández, Devanshi Pandit, Jiaxuan Wang, Kellie Yang, Omolola Fatokun, Mark Berjanskii, Scott MacKay, Tanvir Sajed, Scott Han, Robyn Woudstra, Gina Sykes, Jenna Poelzer, Aadhavya Sivakumaran, Vasuk Gautam, Gane Wong, David S Wishart","doi":"10.1093/nar/gkae1056","DOIUrl":"https://doi.org/10.1093/nar/gkae1056","url":null,"abstract":"MarkerDB (https://markerdb.ca) has become a leading resource for comprehensive information on molecular biomarkers. Over the past 3 years, the database has evolved significantly, reflecting the dynamic landscape of biomarker research and increasing demands from its user community. This year’s update, which is called MarkerDB 2.0, introduces key improvements to enhance the database’s usability, consistency and the range of biomarkers covered. These improvements include (i) the addition of thousands of new biomarkers and associated health conditions, (ii) the inclusion of many new biomarker types and categories, (iii) upgraded searches and data filtering functionalities, (iv) new features for exploring and understanding biomarker panels and (v) significantly expanded and improved descriptions. These upgrades, along with numerous minor improvements in content, interface, layout and overall website performance, have greatly enhanced MarkerDB’s usability and capacity to facilitate biomarker interpretation across various research domains. MarkerDB remains committed to providing a free, publicly accessible platform for consolidated information on a wide range of molecular (protein, genetic, chromosomal and chemical/small molecule) biomarkers, covering diagnostic, prognostic, risk, monitoring, safety and response-related biomarkers. We are confident that these upgrades and updates will improve MarkerDB’s user friendliness, increase its utility and greatly expand its potential applications to many other areas of clinical medicine and biomedical research.","PeriodicalId":19471,"journal":{"name":"Nucleic Acids Research","volume":"10 1","pages":""},"PeriodicalIF":14.9,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142610068","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Epigenetic characterization of adult rhesus monkey spermatogonial stem cells identifies key regulators of stem cell homeostasis","authors":"Rui Bi, Lin-Nuo Pan, Hao Dai, Chunli Sun, Cong Li, Hui-Juan Lin, Lan-Ping Xie, Huai-Xiao Ma, Lin Li, Heng Xie, Kun Guo, Chun-Hui Hou, Yong-Gang Yao, Luo-Nan Chen, Ping Zheng","doi":"10.1093/nar/gkae1013","DOIUrl":"https://doi.org/10.1093/nar/gkae1013","url":null,"abstract":"Spermatogonial stem cells (SSCs) play crucial roles in the preservation of male fertility. However, successful ex vivo expansion of authentic human SSCs remains elusive due to the inadequate understanding of SSC homeostasis regulation. Using rhesus monkeys (Macaca mulatta) as a representative model, we characterized SSCs and progenitor subsets through single-cell RNA sequencing using a cell-specific network approach. We also profiled chromatin status and major histone modifications (H3K4me1, H3K4me3, H3K27ac, H3K27me3 and H3K9me3), and subsequently mapped promoters and active enhancers in TSPAN33+ putative SSCs. Comparing the epigenetic changes between fresh TSPAN33+ cells and cultured TSPAN33+ cells (resembling progenitors), we identified the regulatory elements with higher activity in SSCs, and the potential transcription factors and signaling pathways implicated in SSC regulation. Specifically, TGF-β signaling is activated in monkey putative SSCs. We provided evidence supporting its role in promoting self-renewal of monkey SSCs in culture. Overall, this study outlines the epigenetic landscapes of monkey SSCs and provides clues for optimization of the culture condition for primate SSCs expansion.","PeriodicalId":19471,"journal":{"name":"Nucleic Acids Research","volume":"9 1","pages":""},"PeriodicalIF":14.9,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142610069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Amitava Roy, Ethan Ward, Illyoung Choi, Michele Cosi, Tony Edgin, Travis S Hughes, Md Shafayet Islam, Asif M Khan, Aakash Kolekar, Mariah Rayl, Isaac Robinson, Paul Sarando, Edwin Skidmore, Tyson L Swetnam, Mariah Wall, Zhuoyun Xu, Michelle L Yung, Nirav Merchant, Travis J Wheeler
{"title":"MDRepo—an open data warehouse for community-contributed molecular dynamics simulations of proteins","authors":"Amitava Roy, Ethan Ward, Illyoung Choi, Michele Cosi, Tony Edgin, Travis S Hughes, Md Shafayet Islam, Asif M Khan, Aakash Kolekar, Mariah Rayl, Isaac Robinson, Paul Sarando, Edwin Skidmore, Tyson L Swetnam, Mariah Wall, Zhuoyun Xu, Michelle L Yung, Nirav Merchant, Travis J Wheeler","doi":"10.1093/nar/gkae1109","DOIUrl":"https://doi.org/10.1093/nar/gkae1109","url":null,"abstract":"Molecular Dynamics (MD) simulation of biomolecules provides important insights into conformational changes and dynamic behavior, revealing critical information about folding and interactions with other molecules. The collection of simulations stored in computers across the world holds immense potential to serve as training data for future Machine Learning models that will transform the prediction of structure, dynamics, drug interactions, and more. Ideally, there should exist an open access repository that enables scientists to submit and store their MD simulations of proteins and protein-drug interactions, and to find, retrieve, analyze, and visualize simulations produced by others. However, despite the ubiquity of MD simulation in structural biology, no such repository exists; as a result, simulations are instead stored in scattered locations without uniform metadata or access protocols. Here, we introduce MDRepo, a robust infrastructure that provides a relatively simple process for standardized community contribution of simulations, activates common downstream analyses on stored data, and enables search, retrieval, and visualization of contributed data. MDRepo is built on top of the open-source CyVerse research cyber-infrastructure, and is capable of storing petabytes of simulations, while providing high bandwidth upload and download capabilities and laying a foundation for cloud-based access to its stored data.","PeriodicalId":19471,"journal":{"name":"Nucleic Acids Research","volume":"11 1","pages":""},"PeriodicalIF":14.9,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142610484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ilene Karsch-Mizrachi, Masanori Arita, Tony Burdett, Guy Cochrane, Yasukazu Nakamura, Kim D Pruitt, Valerie A Schneider, On Behalf Of The International Nucleotide Sequence Database Collaboration
{"title":"The international nucleotide sequence database collaboration (INSDC): enhancing global participation.","authors":"Ilene Karsch-Mizrachi, Masanori Arita, Tony Burdett, Guy Cochrane, Yasukazu Nakamura, Kim D Pruitt, Valerie A Schneider, On Behalf Of The International Nucleotide Sequence Database Collaboration","doi":"10.1093/nar/gkae1058","DOIUrl":"https://doi.org/10.1093/nar/gkae1058","url":null,"abstract":"<p><p>The members of the International Nucleotide Sequence Database Collaboration (INSDC; https://insdc.org) have built systems to collect, archive and disseminate sequence data for more than four decades. The three collaborating organizations, the National Library of Medicine, National Center for Biotechnology Information (NLM-NCBI) in the United States, Research Organization of Information and Systems, National Institute of Genetics (ROIS-NIG) in Japan; and the European Molecular Biology Laboratory-European Bioinformatics Institute (EMBL-EBI) formalized their relationship through the adoption of an arrangement which documents their commitment to free and open access to genomic sequences. The INSDC is committed to expand the collaboration to be more representative of the global community of sequences and users. Diversifying participation through new membership will advance open science and data sharing and, in turn, drive innovation. This expansion will additionally benefit the INSDC and its broad user base by providing additional diverse perspectives as it explores emerging areas of data management, including federation, attribution and management.</p>","PeriodicalId":19471,"journal":{"name":"Nucleic Acids Research","volume":" ","pages":""},"PeriodicalIF":16.6,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142624788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Fredrik Tegenfeldt, Dmitry Kuznetsov, Mosè Manni, Matthew Berkeley, Evgeny M Zdobnov, Evgenia V Kriventseva
{"title":"OrthoDB and BUSCO update: annotation of orthologs with wider sampling of genomes","authors":"Fredrik Tegenfeldt, Dmitry Kuznetsov, Mosè Manni, Matthew Berkeley, Evgeny M Zdobnov, Evgenia V Kriventseva","doi":"10.1093/nar/gkae987","DOIUrl":"https://doi.org/10.1093/nar/gkae987","url":null,"abstract":"OrthoDB (https://www.orthodb.org) offers evolutionary and functional annotations of orthologous genes in the widest sampling of eukaryotes, prokaryotes, and viruses, extending experimental gene function knowledge to newly sequenced genomes. We collect gene annotations, delineate hierarchical gene orthology and annotate the orthologous groups (OGs) with functional and evolutionary traits. OrthoDB is the leading resource for species diversity, striving to sample the most diverse and well-researched organisms with the highest quality genomic data. This update expands to include 5827 eukaryotic genomes. We have also added coding DNA sequences (CDSs) and gene loci coordinates. OrthoDB can be browsed, downloaded, or accessed using REST API, SPARQL/RDF and now also via API packages for Python and R Bioconductor. OrthoLoger (https://orthologer.ezlab.org), the tool used for inferring orthologs in OrthoDB, is now available as a Conda package and through BioContainers. ODB-mapper, a component of OrthoLoger, streamlines annotation of genes from newly sequenced genomes with OrthoDB evolutionary and functional descriptors. The benchmarking sets of universal single-copy orthologs (BUSCO), derived from OrthoDB, had correspondingly a major update. The BUSCO tool (https://busco.ezlab.org) has become a standard in genomics, uniquely capable of assessing both eukaryotic and prokaryotic species. It is applicable to gene sets, transcriptomes, genome assemblies and metagenomic bins.","PeriodicalId":19471,"journal":{"name":"Nucleic Acids Research","volume":"14 1","pages":""},"PeriodicalIF":14.9,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142610558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mengwei Li, Kok Siong Ang, Brian Teo, Uddamvathanak Rom, Minh N Nguyen, Sebastian Maurer-Stroh, Jinmiao Chen
{"title":"Rediscovering publicly available single-cell data with the DISCO platform","authors":"Mengwei Li, Kok Siong Ang, Brian Teo, Uddamvathanak Rom, Minh N Nguyen, Sebastian Maurer-Stroh, Jinmiao Chen","doi":"10.1093/nar/gkae1108","DOIUrl":"https://doi.org/10.1093/nar/gkae1108","url":null,"abstract":"Single-cell RNA sequencing (scRNA-seq) has emerged as the key technique for studying transcriptomics at the single-cell level. In our previous work, we presented the DISCO database (https://www.immunesinglecell.org/) that integrates publicly available human scRNA-seq data. We now introduce an enhanced version of DISCO, which has expanded fourfold to include &gt;100 million cells from &gt;17 thousand samples. It provides uniformly realigned read count tables, curated metadata, integrated tissue and phenotype specific atlases, and harmonized cell type annotations. It also hosts a single-cell enhanced knowledgebase of cell type ontology and gene signatures relating to cell types and phenotypes. Lastly, it offers a suite of tools for data retrieval, integration, annotation, and mapping, allowing users to construct customized atlases and perform integrated analysis with their own data. These tools are also available in a standalone R package for offline analysis.","PeriodicalId":19471,"journal":{"name":"Nucleic Acids Research","volume":"7 1","pages":""},"PeriodicalIF":14.9,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142610591","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chia-Chan Hsu, Xiang Yao, Shang-Yao Chen, Tsui-Chun Tsuo, I-Ching Wang
{"title":"The conformation of FOXM1 homodimers in vivo is crucial for regulating transcriptional activities","authors":"Chia-Chan Hsu, Xiang Yao, Shang-Yao Chen, Tsui-Chun Tsuo, I-Ching Wang","doi":"10.1093/nar/gkae988","DOIUrl":"https://doi.org/10.1093/nar/gkae988","url":null,"abstract":"Conformational changes in a transcription factor can significantly affect its transcriptional activity. The activated form of the FOXM1 transcription factor regulates the transcriptional network of genes essential for cell cycle progression and carcinogenesis. However, the mechanism and impact of FOXM1 conformational change on its transcriptional activity in vivo throughout the cell cycle progression remain unexplored. Here, we demonstrate that FOXM1 proteins form novel intermolecular homodimerizations in vivo, and these conformational changes in FOXM1 homodimers impact activity during the cell cycle. Specifically, during the G1 phase, FOXM1 undergoes autorepressive homodimerization, wherein the αβα motif in the C-terminal transcriptional activation domain interacts with the ββαβ motif in the N-terminal repression domain, as evidenced by FRET imaging. Phosphorylation of the αβα motif by PLK1 at S715/S724 disrupts ββαβ–αβα hydrophobic interactions, thereby facilitating a conserved αβα motif switch binding partner to the novel intrinsically disordered regions, leading to FOXM1 autostimulatory homodimerization persisting from the S phase to the G2/M phase in vivo. Furthermore, we identified a minimal ββαβ motif peptide that effectively inhibits cancer cell proliferation both in cell culture and in a mouse tumor model, suggesting a promising autorepression approach for targeting FOXM1 in cancer therapy.","PeriodicalId":19471,"journal":{"name":"Nucleic Acids Research","volume":"44 1","pages":""},"PeriodicalIF":14.9,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142610070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Davide Buzzao, Emma Persson, Dimitri Guala, Erik L L Sonnhammer
{"title":"FunCoup 6: advancing functional association networks across species with directed links and improved user experience","authors":"Davide Buzzao, Emma Persson, Dimitri Guala, Erik L L Sonnhammer","doi":"10.1093/nar/gkae1021","DOIUrl":"https://doi.org/10.1093/nar/gkae1021","url":null,"abstract":"FunCoup 6 (https://funcoup.org) represents a significant advancement in global functional association networks, aiming to provide researchers with a comprehensive view of the functional coupling interactome. This update introduces novel methodologies and integrated tools for improved network inference and analysis. Major new developments in FunCoup 6 include vastly expanding the coverage of gene regulatory links, a new framework for bin-free Bayesian training and a new website. FunCoup 6 integrates a new tool for disease and drug target module identification using the TOPAS algorithm. To expand the utility of the resource for biomedical research, it incorporates pathway enrichment analysis using the ANUBIX and EASE algorithms. The unique comparative interactomics analysis in FunCoup provides insights of network conservation, now allowing users to align orthologs only or query each species network independently. Bin-free training was applied to 23 primary species, and in addition, networks were generated for all remaining 618 species in InParanoiDB 9. Accompanying these advancements, FunCoup 6 features a new redesigned website, together with updated API functionalities, and represents a pivotal step forward in functional genomics research, offering unique capabilities for exploring the complex landscape of protein interactions.","PeriodicalId":19471,"journal":{"name":"Nucleic Acids Research","volume":"72 1","pages":""},"PeriodicalIF":14.9,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142601044","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}